Nikolay Malkin
35 papers · 2020–2025 · 10 conferences · across top CS/AI conferences
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Conferences
ICLR (9)
ICML (9)
NIPS (6)
ACL (3)
UAI (3)
AISTATS (1)
CORL (1)
ECCV (1)
EMNLP (1)
NAACL (1)
Top co-authors
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