Structured Prediction Models for Chord Transcription of Music Audio. - Adrian Weller; Daniel P. W. Ellis; Tony Jebara (ICMLA, 2009)

Bethe Bounds and Approximating the Global Optimum. - Adrian Weller; Tony Jebara (AISTATS, 2013)

On MAP Inference by MWSS on Perfect Graphs. - Adrian Weller; Tony Jebara (UAI, 2013)

Clamping Variables and Approximate Inference. - Adrian Weller; Tony Jebara (NIPS, 2014)

Approximating the Bethe Partition Function. - Adrian Weller; Tony Jebara (UAI, 2014)

Understanding the Bethe Approximation: When and How can it go Wrong? - Adrian Weller; Kui Tang; Tony Jebara; David A. Sontag (UAI, 2014)

Methods for Inference in Graphical Models. - Adrian Weller (2014)

Revisiting the Limits of MAP Inference by MWSS on Perfect Graphs. - Adrian Weller (AISTATS, 2015)

Bethe and Related Pairwise Entropy Approximations. - Adrian Weller (UAI, 2015)

Clamping Improves TRW and Mean Field Approximations. - Adrian Weller; Justin Domke (AISTATS, 2016)

Tightness of LP Relaxations for Almost Balanced Models. - Adrian Weller; Mark Rowland 001; David A. Sontag (AISTATS, 2016)

Train and Test Tightness of LP Relaxations in Structured Prediction. - Ofer Meshi; Mehrdad Mahdavi; Adrian Weller; David A. Sontag (ICML, 2016)

Uprooting and Rerooting Graphical Models. - Adrian Weller (ICML, 2016)

Characterizing Tightness of LP Relaxations by Forbidding Signed Minors. - Adrian Weller (UAI, 2016)

Conditions beyond treewidth for tightness of higher-order LP relaxations. - Mark Rowland 001; Aldo Pacchiano; Adrian Weller (AISTATS, 2017)

Lost Relatives of the Gumbel Trick. - Matej Balog; Nilesh Tripuraneni; Zoubin Ghahramani; Adrian Weller (ICML, 2017)

Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning. - Rowan McAllister; Yarin Gal; Alex Kendall; Mark van der Wilk; Amar Shah 001; Roberto Cipolla; Adrian Weller (IJCAI, 2017)

The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings. - Krzysztof Marcin Choromanski; Mark Rowland 001; Adrian Weller (NIPS, 2017)

Uprooting and Rerooting Higher-Order Graphical Models. - Mark Rowland 001; Adrian Weller (NIPS, 2017)

From Parity to Preference-based Notions of Fairness in Classification. - Muhammad Bilal Zafar; Isabel Valera; Manuel Gomez-Rodriguez; Krishna P. Gummadi; Adrian Weller (NIPS, 2017)

Mapping Intelligence: Requirements and Possibilities. - Sankalp Bhatnagar; Anna Alexandrova; Shahar Avin; Stephen Cave; Lucy Cheke; Matthew Crosby; Jan Feyereisl; Marta Halina; Bao Sheng Loe; Seán Ó hÉigeartaigh; Fernando Martínez-Plumed; Huw Price; et al. (PT-AI, 2017)

On Fairness, Diversity and Randomness in Algorithmic Decision Making. - Nina Grgic-Hlaca; Muhammad Bilal Zafar; Krishna P. Gummadi; Adrian Weller (CoRR, 2017)

Challenges for Transparency. - Adrian Weller (CoRR, 2017)

Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017). - Been Kim; Dmitry M. Malioutov; Kush R. Varshney; Adrian Weller (CoRR, 2017)

Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning. - Nina Grgic-Hlaca; Muhammad Bilal Zafar; Krishna P. Gummadi; Adrian Weller (AAAI, 2018)

Purple Feed: Identifying High Consensus News Posts on Social Media. - Mahmoudreza Babaei; Juhi Kulshrestha; Abhijnan Chakraborty; Fabrício Benevenuto; Krishna P. Gummadi; Adrian Weller (AIES, 2018)

Gauged Mini-Bucket Elimination for Approximate Inference. - Sungsoo Ahn; Michael Chertkov; Jinwoo Shin; Adrian Weller (AISTATS, 2018)

The Geometry of Random Features. - Krzysztof Choromanski; Mark Rowland 001; Tamás Sarlós; Vikas Sindhwani; Richard E. Turner; Adrian Weller (AISTATS, 2018)

Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. - Tameem Adel; Zoubin Ghahramani; Adrian Weller (ICML, 2018)

Bucket Renormalization for Approximate Inference. - Sungsoo Ahn; Michael Chertkov; Adrian Weller; Jinwoo Shin (ICML, 2018)

Structured Evolution with Compact Architectures for Scalable Policy Optimization. - Krzysztof Choromanski; Mark Rowland 001; Vikas Sindhwani; Richard E. Turner; Adrian Weller (ICML, 2018)

Blind Justice: Fairness with Encrypted Sensitive Attributes. - Niki Kilbertus; Adrià Gascón; Matt J. Kusner; Michael Veale; Krishna P. Gummadi; Adrian Weller (ICML, 2018)

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices. - Till Speicher; Hoda Heidari; Nina Grgic-Hlaca; Krishna P. Gummadi; Adish Singla; Adrian Weller; Muhammad Bilal Zafar (KDD, 2018)

Geometrically Coupled Monte Carlo Sampling. - Mark Rowland 001; Krzysztof Choromanski; François Chalus; Aldo Pacchiano; Tamás Sarlós; Richard E. Turner; Adrian Weller (NeurIPS, 2018)

Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction. - Nina Grgic-Hlaca; Elissa M. Redmiles; Krishna P. Gummadi; Adrian Weller (WWW, 2018)

Proceedings of the 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018). - Been Kim; Kush R. Varshney; Adrian Weller (CoRR, 2018)

One-Network Adversarial Fairness. - Tameem Adel; Isabel Valera; Zoubin Ghahramani; Adrian Weller (AAAI, 2019)

Orthogonal Estimation of Wasserstein Distances. - Mark Rowland 001; Jiri Hron; Yunhao Tang; Krzysztof Choromanski; Tamás Sarlós; Adrian Weller (AISTATS, 2019)

TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning. - Tameem Adel; Adrian Weller (ICML, 2019)

Unifying Orthogonal Monte Carlo Methods. - Krzysztof Choromanski; Mark Rowland 001; Wenyu Chen 003; Adrian Weller (ICML, 2019)

Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems: Directions and Differences. - Justus Bogner; Adrian Weller; Stefan Wagner 001; Alfred Zimmermann (Microservices, 2019)

Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models. - Yunfei Teng; Wenbo Gao; François Chalus; Anna Choromanska; Donald Goldfarb; Adrian Weller (NeurIPS, 2019)

The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. - Niki Kilbertus; Philip J. Ball; Matt J. Kusner; Adrian Weller; Ricardo Silva 001 (UAI, 2019)

Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks. - Julius von Kügelgen; Paul K. Rubenstein; Bernhard Schölkopf; Adrian Weller (CoRR, 2019)

An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision. - Hanchen Wang 002; Nina Grgic-Hlaca; Preethi Lahoti; Krishna P. Gummadi; Adrian Weller (CoRR, 2019)

DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning. - Michiel A. Bakker; Duy Patrick Tu; Humberto Riverón Valdés; Krishna P. Gummadi; Kush R. Varshney; Adrian Weller; Alex Pentland (CoRR, 2019)

Train and Test Tightness of LP Relaxations in Structured Prediction. - Ofer Meshi; Ben London 001; Adrian Weller; David A. Sontag (J. Mach. Learn. Res., 2019)

Motivations and Risks of Machine Ethics. - Stephen Cave; Rune Nyrup; Karina Vold; Adrian Weller (Proc. IEEE, 2019)

Transparency: Motivations and Challenges. - Adrian Weller (Explainable AI, 2019)

Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds. - Michiel A. Bakker; Humberto Riverón Valdés; Duy Patrick Tu; Krishna P. Gummadi; Kush R. Varshney; Adrian Weller; Alex Pentland (SafeAI@AAAI, 2020)

You Shouldn't Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods. - Botty Dimanov; Umang Bhatt; Mateja Jamnik; Adrian Weller (SafeAI@AAAI, 2020)

Human-Centered Approaches to Fair and Responsible AI. - Min Kyung Lee; Nina Grgic-Hlaca; Michael Carl Tschantz; Reuben Binns; Adrian Weller; Michelle Carney; Kori Inkpen (CHI Extended Abstracts, 2020)

Now You See Me (CME): Concept-based Model Extraction. - Dmitry Kazhdan; Botty Dimanov; Mateja Jamnik; Pietro Liò; Adrian Weller (CIKM (Workshops), 2020)

Explainable machine learning in deployment. - Umang Bhatt; Alice Xiang; Shubham Sharma 002; Adrian Weller; Ankur Taly; Yunhan Jia; Joydeep Ghosh; Ruchir Puri; José M. F. Moura; Peter Eckersley (FAT*, 2020)

Stochastic Flows and Geometric Optimization on the Orthogonal Group. - Krzysztof Choromanski; David Cheikhi; Jared Davis; Valerii Likhosherstov; Achille Nazaret; Achraf Bahamou; Xingyou Song; Mrugank Akarte; Jack Parker-Holder; Jacob Bergquist; Yuan Gao 038; Aldo Pacchiano; et al. (ICML, 2020)

Evaluating and Aggregating Feature-based Model Explanations. - Umang Bhatt; Adrian Weller; José M. F. Moura (IJCAI, 2020)

Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks. - Moein Khajehnejad; Ahmad Asgharian Rezaei; Mahmoudreza Babaei; Jessica Hoffmann; Mahdi Jalili; Adrian Weller (IJCAI, 2020)

Ode to an ODE. - Krzysztof Marcin Choromanski; Jared Quincy Davis; Valerii Likhosherstov; Xingyou Song; Jean-Jacques E. Slotine; Jacob Varley; Honglak Lee; Adrian Weller; Vikas Sindhwani (NeurIPS, 2020)

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. - Miles Brundage; Shahar Avin; Jasmine Wang; Haydn Belfield; Gretchen Krueger; Gillian K. Hadfield; Heidy Khlaaf; Jingying Yang; Helen Toner; Ruth Fong; Tegan Maharaj; Pang Wei Koh; et al. (CoRR, 2020)

CWY Parametrization for Scalable Learning of Orthogonal and Stiefel Matrices. - Valerii Likhosherstov; Jared Davis; Krzysztof Choromanski; Adrian Weller (CoRR, 2020)

Dimensions of Diversity in Human Perceptions of Algorithmic Fairness. - Nina Grgic-Hlaca; Adrian Weller; Elissa M. Redmiles (CoRR, 2020)

Time Dependence in Non-Autonomous Neural ODEs. - Jared Quincy Davis; Krzysztof Choromanski; Jake Varley; Honglak Lee; Jean-Jacques E. Slotine; Valerii Likhosterov; Adrian Weller; Ameesh Makadia; Vikas Sindhwani (CoRR, 2020)

Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. - Krzysztof Choromanski; Valerii Likhosherstov; David Dohan; Xingyou Song; Jared Davis; Tamás Sarlós; David Belanger 002; Lucy J. Colwell; Adrian Weller (CoRR, 2020)

UFO-BLO: Unbiased First-Order Bilevel Optimization. - Valerii Likhosherstov; Xingyou Song; Krzysztof Choromanski; Jared Davis; Adrian Weller (CoRR, 2020)

An Ode to an ODE. - Krzysztof Choromanski; Jared Quincy Davis; Valerii Likhosherstov; Xingyou Song; Jean-Jacques E. Slotine; Jacob Varley; Honglak Lee; Adrian Weller; Vikas Sindhwani (CoRR, 2020)

Machine Learning Explainability for External Stakeholders. - Umang Bhatt; McKane Andrus; Adrian Weller; Alice Xiang (CoRR, 2020)

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. - Umang Bhatt; Yunfeng Zhang; Javier Antorán; Q. Vera Liao; Prasanna Sattigeri; Riccardo Fogliato; Gabrielle Gauthier Melançon; Ranganath Krishnan; Jason Stanley; Omesh Tickoo; Lama Nachman; Rumi Chunara; et al. (CoRR, 2020)

Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training. - Andrei Margeloiu; Nikola Simidjievski; Mateja Jamnik; Adrian Weller (CoRR, 2020)

Leveraging Data Science to Combat COVID-19: A Comprehensive Review. - Siddique Latif; Muhammad Usman 026; Sanaullah Manzoor; Waleed Iqbal; Junaid Qadir 001; Gareth Tyson; Ignacio Castro; Adeel Razi; Maged N. Kamel Boulos; Adrian Weller; Jon Crowcroft (IEEE Trans. Artif. Intell., 2020)

Beyond Reasonable Doubt: Improving Fairness in Budget-Constrained Decision Making using Confidence Thresholds. - Michiel A. Bakker; Duy Patrick Tu; Krishna P. Gummadi; Alex 'Sandy' Pentland; Kush R. Varshney; Adrian Weller (AIES, 2021)

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. - Umang Bhatt; Javier Antorán; Yunfeng Zhang; Q. Vera Liao; Prasanna Sattigeri; Riccardo Fogliato; Gabrielle Gauthier Melançon; Ranganath Krishnan; Jason Stanley; Omesh Tickoo; Lama Nachman; Rumi Chunara; et al. (AIES, 2021)

Machine Learning and the Meaning of Equal Treatment. - Joshua Simons; Sophia Adams Bhatti; Adrian Weller (AIES, 2021)

CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices. - Valerii Likhosherstov; Jared Davis; Krzysztof Choromanski; Adrian Weller (AISTATS, 2021)

Learning with Hyperspherical Uniformity. - Weiyang Liu; Rongmei Lin; Zhen Liu 019; Li Xiong 001; Bernhard Schölkopf; Adrian Weller (AISTATS, 2021)

Fast conformal classification using influence functions. - Umang Bhatt; Adrian Weller; Giovanni Cherubin (COPA, 2021)

Orthogonal Over-Parameterized Training. - Weiyang Liu; Rongmei Lin; Zhen Liu 019; James M. Rehg; Liam Paull; Li Xiong 001; Le Song; Adrian Weller (CVPR, 2021)

An Algorithmic Framework for Positive Action. - Oliver Thomas 002; Miri Zilka; Adrian Weller; Novi Quadrianto (EAAMO, 2021)

Getting a CLUE: A Method for Explaining Uncertainty Estimates. - Javier Antorán; Umang Bhatt; Tameem Adel; Adrian Weller; José Miguel Hernández-Lobato (ICLR, 2021)

Rethinking Attention with Performers. - Krzysztof Marcin Choromanski; Valerii Likhosherstov; David Dohan; Xingyou Song; Andreea Gane; Tamás Sarlós; Peter Hawkins; Jared Quincy Davis; Afroz Mohiuddin; Lukasz Kaiser; David Benjamin Belanger; Lucy J. Colwell; et al. (ICLR, 2021)

Debiasing a First-order Heuristic for Approximate Bi-level Optimization. - Valerii Likhosherstov; Xingyou Song; Krzysztof Choromanski; Jared Quincy Davis; Adrian Weller (ICML, 2021)

Sub-Linear Memory: How to Make Performers SLiM. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Jared Quincy Davis; Xingyou Song; Adrian Weller (NeurIPS, 2021)

Iterative Teaching by Label Synthesis. - Weiyang Liu; Zhen Liu 019; Hanchen Wang 002; Liam Paull; Bernhard Schölkopf; Adrian Weller (NeurIPS, 2021)

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch. - Luca Viano; Yu-Ting Huang 003; Parameswaran Kamalaruban; Adrian Weller; Volkan Cevher (NeurIPS, 2021)

Unlocking Pixels for Reinforcement Learning via Implicit Attention. - Krzysztof Choromanski; Deepali Jain; Jack Parker-Holder; Xingyou Song; Valerii Likhosherstov; Anirban Santara; Aldo Pacchiano; Yunhao Tang; Adrian Weller (CoRR, 2021)

δ-CLUE: Diverse Sets of Explanations for Uncertainty Estimates. - Dan Ley; Umang Bhatt; Adrian Weller (CoRR, 2021)

Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches. - Dmitry Kazhdan; Botty Dimanov; Helena Andrés-Terré; Mateja Jamnik; Pietro Liò; Adrian Weller (CoRR, 2021)

Do Concept Bottleneck Models Learn as Intended? - Andrei Margeloiu; Matthew Ashman; Umang Bhatt; Yanzhi Chen; Mateja Jamnik; Adrian Weller (CoRR, 2021)

On the Expressive Power of Self-Attention Matrices. - Valerii Likhosherstov; Krzysztof Choromanski; Adrian Weller (CoRR, 2021)

DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement. - Umang Bhatt; Isabel Chien; Muhammad Bilal Zafar; Adrian Weller (CoRR, 2021)

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence. - Xiang Bai; Hanchen Wang 002; Liya Ma; Yongchao Xu; Jiefeng Gan; Ziwei Fan 005; Fan Yang 038; Ke Ma; Jiehua Yang; Song Bai 001; Chang Shu; Xinyu Zou; et al. (CoRR, 2021)

PolyViT: Co-training Vision Transformers on Images, Videos and Audio. - Valerii Likhosherstov; Anurag Arnab; Krzysztof Choromanski; Mario Lucic; Yi Tay; Adrian Weller; Mostafa Dehghani 001 (CoRR, 2021)

Exploring Alignment of Representations with Human Perception. - Vedant Nanda; Ayan Majumdar; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Bradley C. Love; Adrian Weller (CoRR, 2021)

Filling gaps in trustworthy development of AI. - Shahar Avin; Haydn Belfield; Miles Brundage; Gretchen Krueger; Jasmine Wang; Adrian Weller; Markus Anderljung; Igor Krawczuk; David Krueger 001; Jonathan Lebensold; Tegan Maharaj; Noa Zilberman (CoRR, 2021)

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. - Xiang Bai; Hanchen Wang 002; Liya Ma; Yongchao Xu; Jiefeng Gan; Ziwei Fan 005; Fan Yang 038; Ke Ma; Jiehua Yang; Song Bai 001; Chang Shu; Xinyu Zou; et al. (Nat. Mach. Intell., 2021)

CrossWalk: Fairness-Enhanced Node Representation Learning. - Ahmad Khajehnejad; Moein Khajehnejad; Mahmoudreza Babaei; Krishna P. Gummadi; Adrian Weller; Baharan Mirzasoleiman (AAAI, 2022)

On the Fairness of Causal Algorithmic Recourse. - Julius von Kügelgen; Amir-Hossein Karimi; Umang Bhatt; Isabel Valera; Adrian Weller; Bernhard Schölkopf (AAAI, 2022)

Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates. - Dan Ley; Umang Bhatt; Adrian Weller (AAAI, 2022)

Racial Disparities in the Enforcement of Marijuana Violations in the US. - Bradley Butcher; Christopher Robinson; Miri Zilka; Riccardo Fogliato; Carolyn Ashurst; Adrian Weller (AIES, 2022)

Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study. - Miri Zilka; Holli Sargeant; Adrian Weller (AIES, 2022)

Robust Learning from Observation with Model Misspecification. - Luca Viano; Yu-Ting Huang 003; Parameswaran Kamalaruban; Craig Innes; Subramanian Ramamoorthy; Adrian Weller (AAMAS, 2022)

Towards Principled Disentanglement for Domain Generalization. - Hanlin Zhang 002; Yifan Zhang 004; Weiyang Liu; Adrian Weller; Bernhard Schölkopf; Eric P. Xing (CVPR, 2022)

Dimensions of Diversity in Human Perceptions of Algorithmic Fairness. - Nina Grgic-Hlaca; Gabriel Lima; Adrian Weller; Elissa M. Redmiles (EAAMO, 2022)

Structural Causal 3D Reconstruction. - Weiyang Liu; Zhen Liu 019; Liam Paull; Adrian Weller; Bernhard Schölkopf (ECCV (1), 2022)

Multi-disciplinary fairness considerations in machine learning for clinical trials. - Isabel Chien; Nina Deliu; Richard E. Turner; Adrian Weller; Sofia S. Villar; Niki Kilbertus (FAccT, 2022)

Eliciting and Learning with Soft Labels from Every Annotator. - Katherine M. Collins; Umang Bhatt; Adrian Weller (HCOMP, 2022)

Hybrid Random Features. - Krzysztof Marcin Choromanski; Han Lin; Haoxian Chen 002; Arijit Sehanobish; Yuanzhe Ma; Deepali Jain; Jake Varley; Andy Zeng 001; Michael S. Ryoo; Valerii Likhosherstov; Dmitry Kalashnikov; Vikas Sindhwani; et al. (ICLR, 2022)

SphereFace2: Binary Classification is All You Need for Deep Face Recognition. - Yandong Wen; Weiyang Liu; Adrian Weller; Bhiksha Raj; Rita Singh (ICLR, 2022)

From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. - Krzysztof Choromanski; Han Lin; Haoxian Chen 002; Tianyi Zhang; Arijit Sehanobish; Valerii Likhosherstov; Jack Parker-Holder; Tamás Sarlós; Adrian Weller; Thomas Weingarten (ICML, 2022)

Measuring Representational Robustness of Neural Networks Through Shared Invariances. - Vedant Nanda; Till Speicher; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Adrian Weller (ICML, 2022)

On the Utility of Prediction Sets in Human-AI Teams. - Varun Babbar; Umang Bhatt; Adrian Weller (IJCAI, 2022)

Scalable Infomin Learning. - Yanzhi Chen; Weihao Sun; Yingzhen Li; Adrian Weller (NeurIPS, 2022)

Chefs' Random Tables: Non-Trigonometric Random Features. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Kumar Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (NeurIPS, 2022)

Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. - Mateo Espinosa Zarlenga; Pietro Barbiero; Gabriele Ciravegna; Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Zohreh Shams; Frédéric Precioso; Stefano Melacci; Adrian Weller; Pietro Lió; Mateja Jamnik (NeurIPS, 2022)

A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets. - Miri Zilka; Bradley Butcher; Adrian Weller (NeurIPS, 2022)

Partitioned Variational Inference: A Framework for Probabilistic Federated Learning. - Matthew Ashman; Thang D. Bui; Cuong V. Nguyen; Efstratios Markou; Adrian Weller; Siddharth Swaroop; Richard E. Turner (CoRR, 2022)

Synthetic Data - what, why and how? - James Jordon; Lukasz Szpruch; Florimond Houssiau; Mirko Bottarelli; Giovanni Cherubin; Carsten Maple; Samuel N. Cohen; Adrian Weller (CoRR, 2022)

Concept Embedding Models. - Mateo Espinosa Zarlenga; Pietro Barbiero; Gabriele Ciravegna; Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Zohreh Shams; Frédéric Precioso; Stefano Melacci; Adrian Weller; Pietro Liò; Mateja Jamnik (CoRR, 2022)

Can We Automate the Analysis of Online Child Sexual Exploitation Discourse? - Darren Cook; Miri Zilka; Heidi DeSandre; Susan Giles; Adrian Weller; Simon Maskell (CoRR, 2022)

Web-based Elicitation of Human Perception on mixup Data. - Katherine M. Collins; Umang Bhatt; Weiyang Liu; Vihari Piratla; Bradley C. Love; Adrian Weller (CoRR, 2022)

Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. - Xiang Bai; Hanchen Wang 002; Liya Ma; Yongchao Xu; Jiefeng Gan; Ziwei Fan 005; Fan Yang 038; Ke Ma; Jiehua Yang; Song Bai 001; Chang Shu; Xinyu Zou; et al. (Nat. Mach. Intell., 2022)

How transparency modulates trust in artificial intelligence. - John Zerilli; Umang Bhatt; Adrian Weller (Patterns, 2022)

Towards More Robust Interpretation via Local Gradient Alignment. - Sunghwan Joo; Seokhyeon Jeong; Juyeon Heo; Adrian Weller; Taesup Moon (AAAI, 2023)

On the Expressive Flexibility of Self-Attention Matrices. - Valerii Likhosherstov; Krzysztof Choromanski; Adrian Weller (AAAI, 2023)

Approximating Full Conformal Prediction at Scale via Influence Functions. - Javier Abad Martinez; Umang Bhatt; Adrian Weller; Giovanni Cherubin (AAAI, 2023)

Do Invariances in Deep Neural Networks Align with Human Perception? - Vedant Nanda; Ayan Majumdar; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Bradley C. Love; Adrian Weller (AAAI, 2023)

Towards Robust Metrics for Concept Representation Evaluation. - Mateo Espinosa Zarlenga; Pietro Barbiero; Zohreh Shams; Dmitry Kazhdan; Umang Bhatt; Adrian Weller; Mateja Jamnik (AAAI, 2023)

Human Uncertainty in Concept-Based AI Systems. - Katherine Maeve Collins; Matthew Barker; Mateo Espinosa Zarlenga; Naveen Raman 001; Umang Bhatt; Mateja Jamnik; Ilia Sucholutsky; Adrian Weller; Krishnamurthy Dvijotham (AIES, 2023)

Iterative Teaching by Data Hallucination. - Zeju Qiu; Weiyang Liu; Tim Z. Xiao; Zhen Liu 019; Umang Bhatt; Yucen Luo; Adrian Weller; Bernhard Schölkopf (AISTATS, 2023)

Fairness Without Demographic Data: A Survey of Approaches. - Carolyn Ashurst; Adrian Weller (EAAMO, 2023)

FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines. - Matthew Barker; Emma Kallina; Dhananjay Ashok; Katherine M. Collins; Ashley Casovan; Adrian Weller; Ameet Talwalkar; Valerie Chen; Umang Bhatt (EAAMO, 2023)

Media Coverage of Predictive Policing: Bias, Police Engagement, and the Future of Transparency. - Harry Camilleri; Carolyn Ashurst; Nithya Jaisankar; Adrian Weller; Miri Zilka (EAAMO, 2023)

Harms from Increasingly Agentic Algorithmic Systems. - Alan Chan; Rebecca Salganik; Alva Markelius; Chris Pang; Nitarshan Rajkumar; Dmitrii Krasheninnikov; Lauro Langosco; Zhonghao He; Yawen Duan; Micah Carroll; Michelle P. Lin; Alex Mayhew; et al. (FAccT, 2023)

The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments. - Miri Zilka; Riccardo Fogliato; Jiri Hron; Bradley Butcher; Carolyn Ashurst; Adrian Weller (FAccT, 2023)

Pairwise Similarity Learning is SimPLE. - Yandong Wen; Weiyang Liu; Yao Feng 001; Bhiksha Raj; Rita Singh; Adrian Weller; Michael J. Black; Bernhard Schölkopf (ICCV, 2023)

Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap. - Weiyang Liu; Longhui Yu; Adrian Weller; Bernhard Schölkopf (ICLR, 2023)

GeValDi: Generative Validation of Discriminative Models. - Vivek Palaniappan; Matthew Ashman; Katherine M. Collins; Juyeon Heo; Adrian Weller; Umang Bhatt (Tiny Papers @ ICLR, 2023)

Confidential-PROFITT: Confidential PROof of FaIr Training of Trees. - Ali Shahin Shamsabadi; Sierra Calanda Wyllie; Nicholas Franzese; Natalie Dullerud; Sébastien Gambs; Nicolas Papernot; Xiao Wang 012; Adrian Weller (ICLR, 2023)

Robust Explanation Constraints for Neural Networks. - Matthew Wicker; Juyeon Heo; Luca Costabello; Adrian Weller (ICLR, 2023)

Is Learning Summary Statistics Necessary for Likelihood-free Inference? - Yanzhi Chen; Michael U. Gutmann; Adrian Weller (ICML, 2023)

Efficient Graph Field Integrators Meet Point Clouds. - Krzysztof Marcin Choromanski; Arijit Sehanobish; Han Lin; Yunfan Zhao; Eli Berger; Tetiana Parshakova; Alvin Pan; David Watkins; Tianyi Zhang; Valerii Likhosherstov; Somnath Basu Roy Chowdhury; Kumar Avinava Dubey; et al. (ICML, 2023)

Simplex Random Features. - Isaac Reid; Krzysztof Marcin Choromanski; Valerii Likhosherstov; Adrian Weller (ICML, 2023)

Physics-Based Decoding Improves Magnetic Resonance Fingerprinting. - Juyeon Heo; Pingfan Song; Weiyang Liu; Adrian Weller (MICCAI (2), 2023)

Use perturbations when learning from explanations. - Juyeon Heo; Vihari Piratla; Matthew Wicker; Adrian Weller (NeurIPS, 2023)

Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Kumar Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (NeurIPS, 2023)

Diffused Redundancy in Pre-trained Representations. - Vedant Nanda; Till Speicher; John P. Dickerson; Krishna P. Gummadi; Soheil Feizi; Adrian Weller (NeurIPS, 2023)

Controlling Text-to-Image Diffusion by Orthogonal Finetuning. - Zeju Qiu; Weiyang Liu; Haiwen Feng; Yuxuan Xue; Yao Feng 001; Zhen Liu 019; Dan Zhang; Adrian Weller; Bernhard Schölkopf (NeurIPS, 2023)

Quasi-Monte Carlo Graph Random Features. - Isaac Reid; Adrian Weller; Krzysztof Marcin Choromanski (NeurIPS, 2023)

Certification of Distributional Individual Fairness. - Matthew Wicker; Vihari Piratla; Adrian Weller (NeurIPS, 2023)

Learning to Receive Help: Intervention-Aware Concept Embedding Models. - Mateo Espinosa Zarlenga; Katie Collins; Krishnamurthy Dvijotham; Adrian Weller; Zohreh Shams; Mateja Jamnik (NeurIPS, 2023)

Human-in-the-Loop Mixup. - Katherine M. Collins; Umang Bhatt; Weiyang Liu; Vihari Piratla; Ilia Sucholutsky; Bradley C. Love; Adrian Weller (UAI, 2023)

Mnemonist: Locating Model Parameters that Memorize Training Examples. - Ali Shahin Shamsabadi; Jamie Hayes; Borja Balle; Adrian Weller (UAI, 2023)

On the informativeness of supervision signals. - Ilia Sucholutsky; Ruairidh M. Battleday; Katherine M. Collins; Raja Marjieh; Joshua C. Peterson; Pulkit Singh; Umang Bhatt; Nori Jacoby; Adrian Weller; Thomas L. Griffiths 001 (UAI, 2023)

FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features. - Valerii Likhosherstov; Krzysztof Choromanski; Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (CoRR, 2023)

Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents. - Bradley Butcher; Miri Zilka; Darren Cook; Jiri Hron; Adrian Weller (CoRR, 2023)

Robust Learning from Explanations. - Juyeon Heo; Vihari Piratla; Matthew Wicker; Adrian Weller (CoRR, 2023)

Evaluating Language Models for Mathematics through Interactions. - Katherine M. Collins; Albert Q. Jiang; Simon Frieder; Lionel Wong; Miri Zilka; Umang Bhatt; Thomas Lukasiewicz; Yuhuai Wu; Joshua B. Tenenbaum; William Hart; Timothy Gowers; Wenda Li; et al. (CoRR, 2023)

Selective Concept Models: Permitting Stakeholder Customisation at Test-Time. - Matthew Barker; Katherine M. Collins; Krishnamurthy Dvijotham; Adrian Weller; Umang Bhatt (CoRR, 2023)

The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs. - Lance Ying; Katherine M. Collins; Megan Wei; Cedegao E. Zhang; Tan Zhi-Xuan; Adrian Weller; Joshua B. Tenenbaum; Lionel Wong (CoRR, 2023)

The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence. - Hector Zenil; Jesper Tegnér; Felipe S. Abrahão; Alexander Lavin; Vipin Kumar 001; Jeremy G. Frey; Adrian Weller; Larisa N. Soldatova; Alan R. Bundy; Nicholas R. Jennings; Koichi Takahashi; Lawrence Hunter; et al. (CoRR, 2023)

Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey. - Victoria Smith; Ali Shahin Shamsabadi; Carolyn Ashurst; Adrian Weller (CoRR, 2023)

Universal Graph Random Features. - Isaac Reid; Krzysztof Choromanski; Eli Berger; Adrian Weller (CoRR, 2023)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

AI for Mathematics: A Cognitive Science Perspective. - Cedegao E. Zhang; Katherine M. Collins; Adrian Weller; Joshua B. Tenenbaum (CoRR, 2023)

Amortised Inference in Neural Networks for Small-Scale Probabilistic Meta-Learning. - Matthew Ashman; Tommy Rochussen; Adrian Weller (CoRR, 2023)

Estimation of Concept Explanations Should be Uncertainty Aware. - Vihari Piratla; Juyeon Heo; Sukriti Singh; Adrian Weller (CoRR, 2023)

SphereFace Revived: Unifying Hyperspherical Face Recognition. - Weiyang Liu; Yandong Wen; Bhiksha Raj; Rita Singh; Adrian Weller (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Continual Learning by Modeling Intra-Class Variation. - Longhui Yu; Tianyang Hu; Lanqing Hong; Zhen Liu 019; Adrian Weller; Weiyang Liu (Trans. Mach. Learn. Res., 2023)

Self-Guided Belief Propagation - A Homotopy Continuation Method. - Christian Knoll 002; Adrian Weller; Franz Pernkopf (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Perspectives on incorporating expert feedback into model updates. - Valerie Chen; Umang Bhatt; Hoda Heidari; Adrian Weller; Ameet Talwalkar (Patterns, 2023)

In-Context In-Context Learning with Transformer Neural Processes. - Matthew Ashman; Cristiana Diaconu; Adrian Weller; Richard E. Turner (AABI, 2024)

Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation. - Katherine M. Collins; Najoung Kim; Yonatan Bitton; Verena Rieser; Shayegan Omidshafiei; Yushi Hu; Sherol Chen; Senjuti Dutta; Minsuk Chang; Kimin Lee; Youwei Liang; Georgina Evans; et al. (AIES (1), 2024)

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. - Krzysztof Choromanski; Shanda Li; Valerii Likhosherstov; Kumar Avinava Dubey; Shengjie Luo; Di He 001; Yiming Yang; Tamás Sarlós; Thomas Weingarten; Adrian Weller (AISTATS, 2024)

ALVIN: Active Learning Via INterpolation. - Michalis Korakakis; Andreas Vlachos 003; Adrian Weller (EMNLP, 2024)

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization. - Weiyang Liu; Zeju Qiu; Yao Feng 001; Yuliang Xiu; Yuxuan Xue; Longhui Yu; Haiwen Feng; Zhen Liu 019; Juyeon Heo; Songyou Peng; Yandong Wen; Michael J. Black; et al. (ICLR, 2024)

Repelling Random Walks. - Isaac Reid; Eli Berger; Krzysztof Marcin Choromanski; Adrian Weller (ICLR, 2024)

General Graph Random Features. - Isaac Reid; Krzysztof Marcin Choromanski; Eli Berger; Adrian Weller (ICLR, 2024)

Confidential-DPproof: Confidential Proof of Differentially Private Training. - Ali Shahin Shamsabadi; Gefei Tan; Tudor Cebere; Aurélien Bellet; Hamed Haddadi; Nicolas Papernot; Xiao Wang 012; Adrian Weller (ICLR, 2024)

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. - Longhui Yu; Weisen Jiang; Han Shi; Jincheng Yu; Zhengying Liu; Yu Zhang 006; James T. Kwok; Zhenguo Li; Adrian Weller; Weiyang Liu (ICLR, 2024)

Approximately Equivariant Neural Processes. - Matthew Ashman; Cristiana Diaconu; Adrian Weller; Wessel P. Bruinsma; Richard E. Turner (NeurIPS, 2024)

Large Language Models Must Be Taught to Know What They Don't Know. - Sanyam Kapoor; Nate Gruver; Manley Roberts; Katie Collins; Arka Pal; Umang Bhatt; Adrian Weller; Samuel Dooley; Micah Goldblum; Andrew Gordon Wilson (NeurIPS, 2024)

Computing Power and the Governance of Artificial Intelligence. - Girish Sastry; Lennart Heim; Haydn Belfield; Markus Anderljung; Miles Brundage; Julian Hazell; Cullen O'Keefe; Gillian K. Hadfield; Richard Ngo; Konstantin Pilz; George Gor; Emma Bluemke; et al. (CoRR, 2024)

Variance-Reducing Couplings for Random Features: Perspectives from Optimal Transport. - Isaac Reid; Stratis Markou; Krzysztof Choromanski; Richard E. Turner; Adrian Weller (CoRR, 2024)

Representational Alignment Supports Effective Machine Teaching. - Ilia Sucholutsky; Katherine M. Collins; Maya Malaviya; Nori Jacoby; Weiyang Liu; Theodore R. Sumers; Michalis Korakakis; Umang Bhatt; Mark K. Ho; Joshua B. Tenenbaum; Bradley C. Love; Zachary A. Pardos; et al. (CoRR, 2024)

Certificates of Differential Privacy and Unlearning for Gradient-Based Training. - Matthew Wicker; Philip Sosnin; Adrianna Janik; Mark N. Müller; Adrian Weller; Calvin Tsay (CoRR, 2024)

Modulating Language Model Experiences through Frictions. - Katherine M. Collins; Valerie Chen; Ilia Sucholutsky; Hannah Rose Kirk; Malak Sadek; Holli Sargeant; Ameet Talwalkar; Adrian Weller; Umang Bhatt (CoRR, 2024)

People use fast, goal-directed simulation to reason about novel games. - Cedegao E. Zhang; Katherine M. Collins; Lionel Wong; Adrian Weller; Joshua B. Tenenbaum (CoRR, 2024)

Building Machines that Learn and Think with People. - Katherine M. Collins; Ilia Sucholutsky; Umang Bhatt; Kartik Chandra; Lionel Wong; Mina Lee 002; Cedegao E. Zhang; Tan Zhi-Xuan; Mark K. Ho; Vikash Mansinghka 001; Adrian Weller; Joshua B. Tenenbaum; et al. (CoRR, 2024)

Mutual Information Multinomial Estimation. - Yanzhi Chen; Zijing Ou; Adrian Weller; Yingzhen Li (CoRR, 2024)

On the Weaknesses of Backdoor-based Model Watermarking: An Information-theoretic Perspective. - Aoting Hu; Yanzhi Chen; Renjie Xie; Adrian Weller (CoRR, 2024)

On Evaluating LLMs' Capabilities as Functional Approximators: A Bayesian Perspective. - Shoaib Ahmed Siddiqui; Yanzhi Chen; Juyeon Heo; Menglin Xia; Adrian Weller (CoRR, 2024)

Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data. - Matthew Ashman; Cristiana Diaconu; Eric Langezaal; Adrian Weller; Richard E. Turner (CoRR, 2024)

Countering Autonomous Cyber Threats. - Kade M. Heckel; Adrian Weller (CoRR, 2024)

Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning. - Simon Frieder; Jonas Bayer; Katherine M. Collins; Julius Berner; Jacob Loader; András Juhász; Fabian Ruehle; Sean Welleck; Gabriel Poesia; Ryan-Rhys Griffiths; Adrian Weller; Anirudh Goyal; et al. (CoRR, 2024)

AI content detection in the emerging information ecosystem: new obligations for media and tech companies. - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies. - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

Learning Personalized Decision Support Policies. - Umang Bhatt; Valerie Chen; Katherine M. Collins; Parameswaran Kamalaruban; Emma Kallina; Adrian Weller; Ameet Talwalkar (AAAI, 2025)

Mitigating Shortcut Learning with InterpoLated Learning. - Michalis Korakakis; Andreas Vlachos 003; Adrian Weller (ACL (1), 2025)

LLMs on interactive feature collections with implicit dynamic decision strategy. - Juyeon Heo; Vihari Piratla; Kyunghyun Lee 006; Hyonkeun Joh; Adrian Weller (COLING, 2025)

On Evaluating LLMs' Capabilities as Functional Approximators: A Bayesian Evaluation Framework. - Shoaib Ahmed Siddiqui; Yanzhi Chen; Juyeon Heo; Menglin Xia; Adrian Weller (COLING, 2025)

VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning. - Yichao Liang; Nishanth Kumar; Hao Tang 008; Adrian Weller; Joshua B. Tenenbaum; Tom Silver; João F. Henriques; Kevin Ellis (ICLR, 2025)

Can Large Language Models Understand Symbolic Graphics Programs? - Zeju Qiu; Weiyang Liu; Haiwen Feng; Zhen Liu 019; Tim Z. Xiao; Katherine M. Collins; Joshua B. Tenenbaum; Adrian Weller; Michael J. Black; Bernhard Schölkopf (ICLR, 2025)

Linear Transformer Topological Masking with Graph Random Features. - Isaac Reid; Kumar Avinava Dubey; Deepali Jain; William F. Whitney; Amr Ahmed 001; Joshua Ainslie; Alex Bewley; Mithun George Jacob; Aranyak Mehta; David Rendleman; Connor Schenck; Richard E. Turner; et al. (ICLR, 2025)

Variance-Reducing Couplings for Random Features. - Isaac Reid; Stratis Markou; Krzysztof Marcin Choromanski; Richard E. Turner; Adrian Weller (ICLR, 2025)

On Benchmarking Human-Like Intelligence in Machines. - Lance Ying; Katherine M. Collins; Lionel Wong; Ilia Sucholutsky; Ryan Liu 001; Adrian Weller; Tianmin Shu; Thomas L. Griffiths 001; Joshua B. Tenenbaum (CoRR, 2025)

When Should We Orchestrate Multiple Agents? - Umang Bhatt; Sanyam Kapoor; Mihir Upadhyay; Ilia Sucholutsky; Francesco Quinzan; Katherine M. Collins; Adrian Weller; Andrew Gordon Wilson; Muhammad Bilal Zafar (CoRR, 2025)

Ankle Kinematics Estimation Using Artificial Neural Network and Multimodal IMU Data. - Lefan Wang; Pingfan Song; Thomas Stone; Adrian Weller; Sebastian W. Pattinson (IEEE J. Biomed. Health Informatics, 2025)

PoE-World: Compositional World Modeling with Products of Programmatic Experts. - Wasu Top Piriyakulkij; Yichao Liang; Hao Tang 008; Adrian Weller; Marta Kryven; Kevin Ellis (CoRR, 2025)

Identifying, Evaluating, and Mitigating Risks of AI Thought Partnerships. - Kerem Oktar; Katherine M. Collins; José Hernández-Orallo; Diane Coyle; Stephen Cave; Adrian Weller; Ilia Sucholutsky (CoRR, 2025)

From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization. - Shoaib Ahmed Siddiqui; Adrian Weller; David Krueger 001; Gintare Karolina Dziugaite; Michael Curtis Mozer; Eleni Triantafillou (CoRR, 2025)

Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention. - Stephan Rabanser; Ali Shahin Shamsabadi; Olive Franzese; Xiao Wang 012; Adrian Weller; Nicolas Papernot (CoRR, 2025)

Orthogonal Finetuning Made Scalable. - Zeju Qiu; Weiyang Liu; Adrian Weller; Bernhard Schölkopf (CoRR, 2025)

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models. - Lionel Wong; Katherine M. Collins; Lance Ying; Cedegao E. Zhang; Adrian Weller; Tobias Gerstenberg; Timothy O'Donnell; Alexander K. Lew; Jacob Andreas; Joshua B. Tenenbaum; Tyler Brooke-Wilson (CoRR, 2025)

Assessing Adaptive World Models in Machines with Novel Games. - Lance Ying; Katherine M. Collins; Prafull Sharma; Cedric Colas; Kaiya Ivy Zhao; Adrian Weller; Zenna Tavares; Phillip Isola; Samuel J. Gershman; Jacob Andreas; Thomas L. Griffiths 001; François Chollet; et al. (CoRR, 2025)

Empathy in Explanation. - Katherine M. Collins; Kartik Chandra; Adrian Weller; Jonathan Ragan-Kelley; Joshua B. Tenenbaum (CoRR, 2025)

Context-specific certification of AI systems: a pilot in the financial industry. - Kendall Brogle; Emma Kallina; Holli Sargeant; Var Shankar; Adrian Weller; Ashley Casovan; Umang Bhatt (AI Ethics, 2025)

Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AI. - Holli Sargeant; Mackenzie Jorgensen; Arina Shah; Adrian Weller; Umang Bhatt (CoRR, 2025)

Generation and Evaluation in the Human Invention Process through the Lens of Game Design. - Katherine M. Collins; Graham Todd; Cedegao E. Zhang; Adrian Weller; Julian Togelius; Junyi Chu; Lionel Wong; Thomas L. Griffiths 001; Joshua B. Tenenbaum (CoRR, 2025)

Documenting Deployment with Fabric: A Repository of Real-World AI Governance. - Mackenzie Jorgensen; Kendall Brogle; Katherine M. Collins; Lujain Ibrahim; Arina Shah; Petra Ivanovic; Noah Broestl; Gabriel Piles; Paul Dongha; Hatim Abdulhussein; Adrian Weller; Jillian Powers; et al. (CoRR, 2025)