Primeclimb: Designing to Facilitate Mediated Collaborative Inquiry. - James Dai; Mike Wu; Jonathan Cohen; Maria M. Klawe (CSCL, 2003)

Decomposition of speech into voiced and unvoiced components based on a state-space signal model. - Mark Thomson; Simon Boland; Mike Wu; Julien Epps; Michael Smithers (ICASSP (1), 2003)

Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays. - Mike Wu; Ravin Balakrishnan (UIST, 2003)

Participatory design with individuals who have amnesia. - Mike Wu; Brian Richards; Ronald Baecker (PDC, 2004)

Participatory design of an orientation aid for amnesics. - Mike Wu; Ronald Baecker; Brian Richards (CHI, 2005)

A study of manual gesture-based selection for the PEMMI multimodal transport management interface. - Fang Chen 001; Eric H. C. Choi; Julien Epps; Serge Lichman; Natalie Ruiz; Yu (David) Shi; Ronnie Taib; Mike Wu (ICMI, 2005)

Under My Finger: Human Factors in Pushing and Rotating Documents Across the Table. - Clifton Forlines; Chia Shen; Frédéric Vernier; Mike Wu (INTERACT, 2005)

A study of hand shape use in tabletop gesture interaction. - Julien Epps; Serge Lichman; Mike Wu (CHI Extended Abstracts, 2006)

ViCAT: Visualisation and Interaction on a Collaborative Access Table. - Fang Chen 001; Peter Eades; Julien Epps; Serge Lichman; Benjamin Close; Peter Hutterer; Masahiro Takatsuka; Bruce H. Thomas; Mike Wu (Tabletop, 2006)

Gesture Registration, Relaxation, and Reuse for Multi-Point Direct-Touch Surfaces. - Mike Wu; Chia Shen; Kathy Ryall; Clifton Forlines; Ravin Balakrishnan (Tabletop, 2006)

Informing the Design of Direct-Touch Tabletops. - Chia Shen; Kathy Ryall; Clifton Forlines; Alan Esenther; Frédéric Vernier; Katherine Everitt; Mike Wu; Daniel Wigdor; Meredith Ringel Morris; Mark S. Hancock; Edward Tse (IEEE Computer Graphics and Applications, 2006)

Collaborating to remember: a distributed cognition account of families coping with memory impairments. - Mike Wu; Jeremy P. Birnholtz; Brian Richards; Ronald Baecker; Michael Massimi (CHI, 2008)

Lifelong Interactions - Memory impairment is a family affair. - Mike Wu (Interactions, 2008)

An exploration of social requirements for exercise group formation. - Mike Wu; Abhishek Ranjan; Khai N. Truong (CHI, 2009)

Field evaluation of a collaborative memory aid for persons with amnesia and their family members. - Mike Wu; Ronald M. Baecker; Brian Richards (ASSETS, 2010)

Towards Ease of Building Legos in Assessing eHealth Language Technologies A RESTful Laboratory for Data and Software. - Hanna Suominen; Karl Kreiner; Mike Wu; Leif Hanlen (CLEF (Online Working Notes/Labs/Workshop), 2012)

Financial Market Prediction. - Mike Wu (CoRR, 2015)

Spreadsheet Probabilistic Programming. - Mike Wu; Yura N. Perov; Frank D. Wood; Hongseok Yang (CoRR, 2016)

Position and Vector Detection of Blind Spot motion with the Horn-Schunck Optical Flow. - Stephen Yu; Mike Wu (CoRR, 2016)

Predicting intervention onset in the ICU with switching state space models. - Marzyeh Ghassemi; Mike Wu; Michael C. Hughes; Peter Szolovits; Finale Doshi-Velez (CRI, 2017)

Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database. - Mike Wu; Marzyeh Ghassemi; Mengling Feng; Leo A. Celi; Peter Szolovits; Finale Doshi-Velez (J. Am. Medical Informatics Assoc., 2017)

Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. - Mike Wu; Michael C. Hughes; Sonali Parbhoo; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (AAAI, 2018)

Multimodal Generative Models for Scalable Weakly-Supervised Learning. - Mike Wu; Noah D. Goodman (NeurIPS, 2018)

Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. - Mike Wu; Milan Mosse; Noah D. Goodman; Chris Piech (AAAI, 2019)

Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. - Mike Wu; Noah D. Goodman; Stefano Ermon (AISTATS, 2019)

Pragmatic inference and visual abstraction enable contextual flexibility during visual communication. - Judith W. Fan; Robert X. D. Hawkins; Mike Wu; Noah D. Goodman (CoRR, 2019)

Generative Grading: Neural Approximate Parsing for Automated Student Feedback. - Ali Malik; Mike Wu; Vrinda Vasavada; Jinpeng Song; John Mitchell; Noah D. Goodman; Chris Piech (CoRR, 2019)

Regional Tree Regularization for Interpretability in Black Box Models. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Ryan Kindle; Leo A. Celi; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (CoRR, 2019)

Gradient Boosting Machine: A Survey. - Zhiyuan He; Danchen Lin; Thomas Lau; Mike Wu (CoRR, 2019)

Multimodal Generative Models for Compositional Representation Learning. - Mike Wu; Noah D. Goodman (CoRR, 2019)

Meta-Amortized Variational Inference and Learning. - Mike Wu; Kristy Choi; Noah D. Goodman; Stefano Ermon (AAAI, 2020)

Regional Tree Regularization for Interpretability in Deep Neural Networks. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Ryan Kindle; Leo A. Celi; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (AAAI, 2020)

Variational Item Response Theory: Fast, Accurate, and Expressive. - Mike Wu; Richard Lee Davis; Benjamin W. Domingue; Chris Piech; Noah D. Goodman (EDM, 2020)

On Mutual Information in Contrastive Learning for Visual Representations. - Mike Wu; Chengxu Zhuang; Milan Mosse; Daniel Yamins; Noah D. Goodman (CoRR, 2020)

A Simple Framework for Uncertainty in Contrastive Learning. - Mike Wu; Noah D. Goodman (CoRR, 2020)

HarperValleyBank: A Domain-Specific Spoken Dialog Corpus. - Mike Wu; Jonathan Nafziger; Anthony Scodary; Andrew Maas (CoRR, 2020)

Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems. - Ali Malik; Mike Wu; Vrinda Vasavada; Jinpeng Song; Madison Coots; John Mitchell; Noah D. Goodman; Chris Piech (EDM, 2021)

Viewmaker Networks: Learning Views for Unsupervised Representation Learning. - Alex Tamkin; Mike Wu; Noah D. Goodman (ICLR, 2021)

Conditional Negative Sampling for Contrastive Learning of Visual Representations. - Mike Wu; Milan Mosse; Chengxu Zhuang; Daniel Yamins; Noah D. Goodman (ICLR, 2021)

Improving Compositionality of Neural Networks by Decoding Representations to Inputs. - Mike Wu; Noah D. Goodman; Stefano Ermon (NeurIPS, 2021)

ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback. - Mike Wu; Noah D. Goodman; Chris Piech; Chelsea Finn (CoRR, 2021)

Modeling Item Response Theory with Stochastic Variational Inference. - Mike Wu; Richard Lee Davis; Benjamin W. Domingue; Chris Piech; Noah D. Goodman (CoRR, 2021)

Temperature as Uncertainty in Contrastive Learning. - Oliver Zhang; Mike Wu; Jasmine Bayrooti; Noah D. Goodman (CoRR, 2021)

Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study. - Ananya Karthik; Mike Wu; Noah D. Goodman; Alex Tamkin (CoRR, 2021)

Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Volker Roth 001; Finale Doshi-Velez (J. Artif. Intell. Res., 2021)

Foundation Posteriors for Approximate Probabilistic Inference. - Mike Wu; Noah D. Goodman (NeurIPS, 2022)

Tutela: An Open-Source Tool for Assessing User-Privacy on Ethereum and Tornado Cash. - Mike Wu; Will McTighe; Kaili Wang; István András Seres; Nick Bax; Manuel Puebla; Mariano Mendez; Federico Carrone; Tomás De Mattey; Herman O. Demaestri; Mariano Nicolini; Pedro Fontana (CoRR, 2022)

Know Thy Student: Interactive Learning with Gaussian Processes. - Rose E. Wang; Mike Wu; Noah D. Goodman (CoRR, 2022)

Constant Power Root Market Makers. - Mike Wu; Will McTighe (CoRR, 2022)

Extensions and applications of deep probabilistic inference for generative models. - Mike Wu (2022)