Nikolay Malkin

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 62

Top Topics

Bayesian Inference

Diffusion Models

Graphical Structure

Top Venues

Publications

Anas Krichel, Nikolay Malkin, Salem Lahlou, Yoshua Bengio
On Generalization for Generative Flow Networks. CoRR (2024)
Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
Expected flow networks in stochastic environments and two-player zero-sum games. ICLR (2024)
Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin
On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling. CoRR (2024)
Ming-Yang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio
PhyloGFN: Phylogenetic inference with generative flow networks. ICLR (2024)
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
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR (2024)
Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain
Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR (2024)
Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin
Amortizing intractable inference in large language models. ICLR (2024)
Yoshua Bengio, Nikolay Malkin
Machine learning and information theory concepts towards an AI Mathematician. CoRR (2024)
Pablo Lemos, Sammy Sharief, Nikolay Malkin, Laurence Perreault Levasseur, Yashar Hezaveh
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation. CoRR (2024)
Jean-Pierre Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio
Delta-AI: Local objectives for amortized inference in sparse graphical models. ICLR (2024)
Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio
Discrete Probabilistic Inference as Control in Multi-path Environments. CoRR (2024)
Arian Hosseini, Xingdi Yuan, Nikolay Malkin, Aaron C. Courville, Alessandro Sordoni, Rishabh Agarwal
V-STaR: Training Verifiers for Self-Taught Reasoners. CoRR (2024)
Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
Simulation-Free Schrödinger Bridges via Score and Flow Matching. AISTATS (2024)
Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin
Amortizing intractable inference in diffusion models for vision, language, and control. CoRR (2024)
Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio
Improving and generalizing flow-based generative models with minibatch optimal transport. Trans. Mach. Learn. Res. 2024 (2024)
Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. CoRR (2023)
Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
Expected flow networks in stochastic environments and two-player zero-sum games. CoRR (2023)
Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin
Amortizing intractable inference in large language models. CoRR (2023)
Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin
A theory of continuous generative flow networks. CoRR (2023)
Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability. ICML (2023)
Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio
Better Training of GFlowNets with Local Credit and Incomplete Trajectories. ICML (2023)
Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur
Improving Gradient-guided Nested Sampling for Posterior Inference. CoRR (2023)
Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. NeurIPS (2023)
Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin
A theory of continuous generative flow networks. ICML (2023)
Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
Simulation-free Schrödinger bridges via score and flow matching. CoRR (2023)
Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
GFlowOut: Dropout with Generative Flow Networks. ICML (2023)
Shreshth A. Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal
BatchGFN: Generative Flow Networks for Batch Active Learning. CoRR (2023)
Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio
Better Training of GFlowNets with Local Credit and Incomplete Trajectories. CoRR (2023)
Batu Ozturkler, Nikolay Malkin, Zhen Wang, Nebojsa Jojic
ThinkSum: Probabilistic reasoning over sets using large language models. ACL (1) (2023)
Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio
Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. CoRR (2023)
Jarrid Rector-Brooks, Kanika Madan, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Sarath Chandar, Nikolay Malkin, Yoshua Bengio
Thompson sampling for improved exploration in GFlowNets. CoRR (2023)
Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. NeurIPS (2023)
Andrew Nam, Eric Elmoznino, Nikolay Malkin, Chen Sun, Yoshua Bengio, Guillaume Lajoie
Discrete, compositional, and symbolic representations through attractor dynamics. CoRR (2023)
Jean-Pierre Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio
Delta-AI: Local objectives for amortized inference in sparse graphical models. CoRR (2023)
Mingyang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio
PhyloGFN: Phylogenetic inference with generative flow networks. CoRR (2023)
Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie Everett, Alexandros Graikos, Yoshua Bengio
GFlowNet-EM for learning compositional latent variable models. CoRR (2023)
Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio
GFlowNets and variational inference. ICLR (2023)
Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. CoRR (2023)
Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie E. Everett, Alexandros Graikos, Yoshua Bengio
GFlowNet-EM for Learning Compositional Latent Variable Models. ICML (2023)
Zhuohong Li, Fangxiao Lu, Hongyan Zhang, Lilin Tu, Jiayi Li, Xin Huang, Caleb Robinson, Nikolay Malkin, Nebojsa Jojic, Pedram Ghamisi, Ronny Hänsch, Naoto Yokoya
The Outcome of the 2021 IEEE GRSS Data Fusion Contest - Track MSD: Multitemporal Semantic Change Detection. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15 (2022)
Dinghuai Zhang, Ricky T. Q. Chen, Nikolay Malkin, Yoshua Bengio
Unifying Generative Models with GFlowNets. CoRR (2022)
Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio
GFlowNets and variational inference. CoRR (2022)
Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio
Trajectory Balance: Improved Credit Assignment in GFlowNets. CoRR (2022)
Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio
Generative Flow Networks for Discrete Probabilistic Modeling. ICML (2022)
Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin
Learning GFlowNets from partial episodes for improved convergence and stability. CoRR (2022)
Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
Diffusion Models as Plug-and-Play Priors. NeurIPS (2022)
Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio
Trajectory balance: Improved credit assignment in GFlowNets. NeurIPS (2022)
Alexandre Adam, Adam Coogan, Nikolay Malkin, Ronan Legin, Laurence Perreault Levasseur, Yashar Hezaveh, Yoshua Bengio
Posterior samples of source galaxies in strong gravitational lenses with score-based priors. CoRR (2022)
Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic
Resolving label uncertainty with implicit posterior models. UAI (2022)
Nikolay Malkin, Zhen Wang, Nebojsa Jojic
Coherence boosting: When your pretrained language model is not paying enough attention. ACL (1) (2022)
Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic
Resolving label uncertainty with implicit posterior models. CoRR (2022)
Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
GFlowOut: Dropout with Generative Flow Networks. CoRR (2022)
Batu Ozturkler, Nikolay Malkin, Zhen Wang, Nebojsa Jojic
ThinkSum: Probabilistic reasoning over sets using large language models. CoRR (2022)
Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio
Generative Flow Networks for Discrete Probabilistic Modeling. CoRR (2022)
Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
Diffusion models as plug-and-play priors. CoRR (2022)
Nikolay Malkin, Caleb Robinson, Nebojsa Jojic
High-resolution land cover change from low-resolution labels: Simple baselines for the 2021 IEEE GRSS Data Fusion Contest. CoRR (2021)
Nikolay Malkin, Sameera Lanka, Pranav Goel, Nebojsa Jojic
Studying word order through iterative shuffling. CoRR (2021)
Nebojsa Jojic, Nikolay Malkin, Caleb Robinson, Anthony Ortiz
From Local Algorithms to Global Results: Human-Machine Collaboration for Robust Analysis of Geographically Diverse Imagery. IGARSS (2021)
Nikolay Malkin, Zhen Wang, Nebojsa Jojic
Boosting coherence of language models. CoRR (2021)
Nikolay Malkin, Sameera Lanka, Pranav Goel, Nebojsa Jojic
Studying word order through iterative shuffling. EMNLP (1) (2021)
Nikolay Malkin, Sameera Lanka, Pranav Goel, Sudha Rao, Nebojsa Jojic
GPT Perdetry Test: Generating new meanings for new words. NAACL-HLT (2021)
Nikolay Malkin, Anthony Ortiz, Nebojsa Jojic
Mining Self-similarity: Label Super-Resolution with Epitomic Representations. ECCV (26) (2020)