Walking through sight: Seeing the ability to see, in a 3-D augmediated reality environment. - Ryan E. Janzen; Seyed Nima Yasrebi; Avishek Joey Bose; Arjun Subramanian; Steve Mann 001 (GEM, 2014)

Adversarial Contrastive Estimation. - Avishek Joey Bose; Huan Ling; Yanshuai Cao (ACL (1), 2018)

Adversarial Attacks on Face Detectors Using Neural Net Based Constrained Optimization. - Avishek Joey Bose; Parham Aarabi (MMSP, 2018)

A Cross-Domain Transferable Neural Coherence Model. - Peng Xu; Hamidreza Saghir; Jin Sung Kang; Teng Long; Avishek Joey Bose; Yanshuai Cao; Jackie Chi Kit Cheung (ACL (1), 2019)

Compositional Fairness Constraints for Graph Embeddings. - Avishek Joey Bose; William L. Hamilton (ICML, 2019)

Virtual Fakes: DeepFakes for Virtual Reality. - Avishek Joey Bose; Parham Aarabi (MMSP, 2019)

Generalizable Adversarial Attacks Using Generative Models. - Avishek Joey Bose; Andre Cianflone; William L. Hamilton (CoRR, 2019)

Improving Exploration in Soft-Actor-Critic with Normalizing Flows Policies. - Patrick Nadeem Ward; Ariella Smofsky; Avishek Joey Bose (CoRR, 2019)

Meta-Graph: Few shot Link Prediction via Meta Learning. - Avishek Joey Bose; Ankit Jain; Piero Molino; William L. Hamilton (CoRR, 2019)

Structure Aware Negative Sampling in Knowledge Graphs. - Kian Ahrabian; Aarash Feizi; Yasmin Salehi; William L. Hamilton; Avishek Joey Bose (EMNLP (1), 2020)

Latent Variable Modelling with Hyperbolic Normalizing Flows. - Avishek Joey Bose; Ariella Smofsky; Renjie Liao; Prakash Panangaden; William L. Hamilton (ICML, 2020)

Adversarial Example Games. - Avishek Joey Bose; Gauthier Gidel; Hugo Berard; Andre Cianflone; Pascal Vincent; Simon Lacoste-Julien; William L. Hamilton (NeurIPS, 2020)

Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding. - Nouha Dziri; Andrea Madotto; Osmar Zaïane; Avishek Joey Bose (EMNLP (1), 2021)

Equivariant Discrete Normalizing Flows. - Avishek Joey Bose; Ivan Kobyzev (CoRR, 2021)

Online Adversarial Attacks. - Andjela Mladenovic; Avishek Joey Bose; Hugo Berard; William L. Hamilton; Simon Lacoste-Julien; Pascal Vincent; Gauthier Gidel (ICLR, 2022)

Matching Normalizing Flows and Probability Paths on Manifolds. - Heli Ben-Hamu; Samuel Cohen; Joey Bose; Brandon Amos; Maximilian Nickel; Aditya Grover; Ricky T. Q. Chen; Yaron Lipman (ICML, 2022)

Riemannian Diffusion Models. - Chin-Wei Huang; Milad Aghajohari; Joey Bose; Prakash Panangaden; Aaron C. Courville (NeurIPS, 2022)

Controllable Generative Modeling via Causal Reasoning. - Joey Bose; Ricardo Pio Monti; Aditya Grover (Trans. Mach. Learn. Res., 2022)

A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis. - Damien Ferbach; Christos Tsirigotis; Gauthier Gidel; Avishek Joey Bose (ICLR, 2023)

EDGI: Equivariant Diffusion for Planning with Embodied Agents. - Johann Brehmer; Joey Bose; Pim de Haan; Taco S. Cohen (NeurIPS, 2023)

Feature Likelihood Score: Evaluating the Generalization of Generative Models Using Samples. - Marco Jiralerspong; Avishek Joey Bose; Ian Gemp; Chongli Qin; Yoram Bachrach; Gauthier Gidel (NeurIPS, 2023)

Feature Likelihood Score: Evaluating Generalization of Generative Models Using Samples. - Marco Jiralerspong; Avishek Joey Bose; Gauthier Gidel (CoRR, 2023)

On the Stability of Iterative Retraining of Generative Models on their own Data. - Quentin Bertrand; Avishek Joey Bose; Alexandre Duplessis; Marco Jiralerspong; Gauthier Gidel (ICLR, 2024)

SE(3)-Stochastic Flow Matching for Protein Backbone Generation. - Avishek Joey Bose; Tara Akhound-Sadegh; Guillaume Huguet; Kilian Fatras; Jarrid Rector-Brooks; Cheng-Hao Liu; Andrei Cristian Nica; Maksym Korablyov; Michael M. Bronstein; Alexander Tong 001 (ICLR, 2024)

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. - Tara Akhound-Sadegh; Jarrid Rector-Brooks; Avishek Joey Bose; Sarthak Mittal; Pablo Lemos; Cheng-Hao Liu; Marcin Sendera; Siamak Ravanbakhsh; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Alexander Tong 001 (ICML, 2024)

Fisher Flow Matching for Generative Modeling over Discrete Data. - Oscar Davis; Samuel Kessler; Mircea Petrache; Ismail Ilkan Ceylan; Michael M. Bronstein; Avishek Joey Bose (NeurIPS, 2024)

Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences. - Damien Ferbach; Quentin Bertrand; Avishek Joey Bose; Gauthier Gidel (NeurIPS, 2024)

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation. - Guillaume Huguet; James Vuckovic; Kilian Fatras; Eric Thibodeau-Laufer; Pablo Lemos; Riashat Islam; Cheng-Hao Liu; Jarrid Rector-Brooks; Tara Akhound-Sadegh; Michael M. Bronstein; Alexander Tong 001; Avishek Joey Bose (NeurIPS, 2024)

Metric Flow Matching for Smooth Interpolations on the Data Manifold. - Kacper Kapusniak; Peter Potaptchik; Teodora Reu; Leo Zhang; Alexander Tong 001; Michael M. Bronstein; Avishek Joey Bose; Francesco Di Giovanni (NeurIPS, 2024)

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. - Guillaume Huguet; James Vuckovic; Kilian Fatras; Eric Thibodeau-Laufer; Pablo Lemos; Riashat Islam; Cheng-Hao Liu; Jarrid Rector-Brooks; Tara Akhound-Sadegh; Michael M. Bronstein; Alexander Tong 001; Avishek Joey Bose (CoRR, 2024)

Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. - Jarrid Rector-Brooks; Mohsin Hasan; Zhangzhi Peng; Zachary Quinn; Cheng-Hao Liu; Sarthak Mittal; Nouha Dziri; Michael M. Bronstein; Yoshua Bengio; Pranam Chatterjee; Alexander Tong 001; Avishek Joey Bose (CoRR, 2024)

Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. - Jarrid Rector-Brooks; Mohsin Hasan; Zhangzhi Peng; Cheng-Hao Liu; Sarthak Mittal; Nouha Dziri; Michael M. Bronstein; Pranam Chatterjee; Alexander Tong 001; Joey Bose (ICLR, 2025)

The Superposition of Diffusion Models Using the Itô Density Estimator. - Marta Skreta; Lazar Atanackovic; Joey Bose; Alexander Tong 001; Kirill Neklyudov (ICLR, 2025)

Scalable Equilibrium Sampling with Sequential Boltzmann Generators. - Charlie B. Tan; Avishek Joey Bose; Chen Lin 003; Leon Klein; Michael M. Bronstein; Alexander Tong 001 (CoRR, 2025)

FORT: Forward-Only Regression Training of Normalizing Flows. - Danyal Rehman; Oscar Davis; Jiarui Lu; Jian Tang 005; Michael M. Bronstein; Yoshua Bengio; Alexander Tong 001; Avishek Joey Bose (CoRR, 2025)

RETRO SYNFLOW: Discrete Flow Matching for Accurate and Diverse Single-Step Retrosynthesis. - Robin Yadav; Qi Yan; Guy Wolf; Avishek Joey Bose; Renjie Liao (CoRR, 2025)

Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities. - Tara Akhound-Sadegh; Jungyoon Lee; Avishek Joey Bose; Valentin De Bortoli; Arnaud Doucet; Michael M. Bronstein; Dominique Beaini; Siamak Ravanbakhsh; Kirill Neklyudov; Alexander Tong 001 (CoRR, 2025)