Kirill Neklyudov
15 papers · 2017–2025 · 4 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (32)
🏆
Keyword Champion
(2)
🧭
Keyword Pioneer
💎
Century Club · Bronze
⚡
Prolific Year · Productive
🗃️
Keyword Collector
(85)
Venues
Top co-authors
Research topics
Machine Learning
(13)
Deep Learning
(10)
Optimization & Theory · Machine Learning
(9)
Models
(8)
Mathematics & Optimization
(6)
Optimization
(6)
Artificial Intelligence
(5)
Bayesian & Probabilistic · Machine Learning
(3)
Core AI
(3)
Application Areas
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Core Methods
(2)
Learning Types
(2)
Optimization & Theory · Deep Learning
(2)
Computer Vision
(1)
Keywords
optimal transport
(3)
metropolis-hastings algorithm
(2)
stochastic differential equation
(2)
variational inference
(2)
markov chain monte carlo
(2)
black-box optimization
(2)
diffusion model
(2)
bayesian inference
(1)
importance sampling
(1)
generative modeling
(1)
constrained optimization
(1)
deep learning
(1)
sequential monte carlo
(1)
model pruning
(1)
structured sparsity
(1)
flow matching
(1)
natural gradient descent
(1)
markov chain
(1)
langevin dynamics
(1)
model compression
(1)
Papers
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
AISTATS 2025
Efficient Evolutionary Search Over Chemical Space with Large Language Models
ICLR 2025
Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
ICML 2025
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold
ICLR 2025
The Superposition of Diffusion Models Using the Itô Density Estimator
ICLR 2025
A Computational Framework for Solving Wasserstein Lagrangian Flows
ICML 2024
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
NeurIPS 2024
Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC
ICML 2024
Action Matching: Learning Stochastic Dynamics from Samples
ICML 2023
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation
NeurIPS 2023
Orbital MCMC
AISTATS 2022
Involutive MCMC: a Unifying Framework
ICML 2020
The Implicit Metropolis-Hastings Algorithm
NeurIPS 2019
Variance Networks: When Expectation Does Not Meet Your Expectations
ICLR 2019
Structured Bayesian Pruning via Log-Normal Multiplicative Noise
NeurIPS 2017