← Authors

Nikolay Malkin

35 papers · 2020–2025 · 10 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (10) πŸƒ Academic Marathon (5) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (13) 🀝 Dynamic Duo (25) πŸ‘‘ Triple Crown πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (35) ⚑ Prolific Year (9) πŸ—ƒοΈ Keyword Collector (90) ❓ The Questioner

Conferences

ICLR (9) ICML (9) NIPS (6) ACL (3) UAI (3) AISTATS (1) CORL (1) ECCV (1) EMNLP (1) NAACL (1)

Top co-authors

Yoshua Bengio (25) Moksh Jain (9) Dinghuai Zhang (8) Nebojsa Jojic (7) Pablo Lemos (6) Emmanuel Bengio (5) Minsu Kim (5) Jarrid Rector-Brooks (5) Tristan Deleu (4) Marcin Sendera (4)

Keywords

generative flow network (8) variational inference (5) diffusion model (4) amortized inference (4) large language model (3) probabilistic modeling (3) energy-based model (3) posterior distribution (2) language model (2) credit assignment (2) generative model (2) in-context learning (2) flow matching (2) trajectory balance (2) weakly supervised learning (1) constrained generation (1) optimal transport (1) gradient-based optimization (1) approximate inference (1) image segmentation (1)

Papers

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation ICLR 2025
Mixtures of In-Context Learners ACL 2025
Adaptive teachers for amortized samplers ICLR 2025
Action abstractions for amortized sampling ICLR 2025
Can a Bayesian Oracle Prevent Harm from an Agent? UAI 2025
Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models ICML 2025
Fast Flow-based Visuomotor Policies via Conditional Optimal Transport Couplings CORL 2025
Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning ICLR 2025
Expected flow networks in stochastic environments and two-player zero-sum games ICLR 2024
Amortizing intractable inference in diffusion models for vision, language, and control NIPS 2024
Improved off-policy training of diffusion samplers NIPS 2024
Simulation-Free SchrΓΆdinger Bridges via Score and Flow Matching AISTATS 2024
PhyloGFN: Phylogenetic inference with generative flow networks ICLR 2024
Delta-AI: Local objectives for amortized inference in sparse graphical models ICLR 2024
Amortizing intractable inference in large language models ICLR 2024
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities ICML 2024
Improving Gradient-Guided Nested Sampling for Posterior Inference ICML 2024
Discrete Probabilistic Inference as Control in Multi-path Environments UAI 2024
Better Training of GFlowNets with Local Credit and Incomplete Trajectories ICML 2023
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network NIPS 2023
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets NIPS 2023
GFlowNets and variational inference ICLR 2023
ThinkSum: Probabilistic reasoning over sets using large language models ACL 2023
GFlowNet-EM for Learning Compositional Latent Variable Models ICML 2023
A theory of continuous generative flow networks ICML 2023
GFlowOut: Dropout with Generative Flow Networks ICML 2023
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability ICML 2023
Trajectory balance: Improved credit assignment in GFlowNets NIPS 2022
Coherence boosting: When your pretrained language model is not paying enough attention ACL 2022
Generative Flow Networks for Discrete Probabilistic Modeling ICML 2022
Resolving label uncertainty with implicit posterior models UAI 2022
Diffusion Models as Plug-and-Play Priors NIPS 2022
Studying word order through iterative shuffling EMNLP 2021
GPT Perdetry Test: Generating new meanings for new words NAACL 2021
Mining self-similarity: Label super-resolution with epitomic representations ECCV 2020