Nikolay Malkin

Affiliations

University of Edinburgh

papers

921

total citations

papers (16)

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network

NEURIPS 2023arXiv

citations

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning

ICLR 2025arXiv

citations

PhyloGFN: Phylogenetic inference with generative flow networks

ICLR 2024arXiv

citations

Adaptive teachers for amortized samplers

ICLR 2025arXiv

citations

Improving Gradient-Guided Nested Sampling for Posterior Inference

ICML 2024arXiv

citations

Mining self-similarity: Label super-resolution with epitomic representations

ECCV 2020arXiv

citations

Expected flow networks in stochastic environments and two-player zero-sum games

ICLR 2024arXiv

citations

Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models

ICML 2025arXiv

citations

Delta-AI: Local objectives for amortized inference in sparse graphical models

ICLR 2024arXiv

citations

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation

ICLR 2025arXiv

citations

Action abstractions for amortized sampling

ICLR 2025arXiv

citations

Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets

NEURIPS 2023

citations

Nikolay Malkin

Affiliations

papers (16)

Diffusion Models as Plug-and-Play Priors

Trajectory balance: Improved credit assignment in GFlowNets

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities

Amortizing intractable inference in large language models

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning

PhyloGFN: Phylogenetic inference with generative flow networks

Adaptive teachers for amortized samplers

Improving Gradient-Guided Nested Sampling for Posterior Inference

Mining self-similarity: Label super-resolution with epitomic representations

Expected flow networks in stochastic environments and two-player zero-sum games

Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models

Delta-AI: Local objectives for amortized inference in sparse graphical models

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation

Action abstractions for amortized sampling

Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets

papers (16)

Diffusion Models as Plug-and-Play Priors

Trajectory balance: Improved credit assignment in GFlowNets

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities

Amortizing intractable inference in large language models

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning

PhyloGFN: Phylogenetic inference with generative flow networks

Adaptive teachers for amortized samplers

Improving Gradient-Guided Nested Sampling for Posterior Inference

Mining self-similarity: Label super-resolution with epitomic representations

Expected flow networks in stochastic environments and two-player zero-sum games

Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models

Delta-AI: Local objectives for amortized inference in sparse graphical models

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation

Action abstractions for amortized sampling

Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets