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Neklyudov, Kirill

  1. Action Matching: Learning Stochastic Dynamics from Samples
    2022/10/13 by Kirill Neklyudov, Rob Brekelmans, Neklyudov, Kirill +5 · 1 voice · 14 citations
    Computer Science · #Data Stream Mining Techniques #Gaussian Processes and Bayesian Inference #Time Series Analysis and Forecasting #cs.LG
  2. The Superposition of Diffusion Models Using the Itô Density Estimator
    2024/12/23 by Marta Skreta, Skreta, Marta, Lazar Atanackovic +7 · 5 voices · 10 citations
    Mathematics · #Statistical Methods and Inference
  3. Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
    2025/03/04 by Marta Skreta, Skreta, Marta, Tara Akhound-Sadegh +15 · 21 citations
    Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Opinion Dynamics and Social Influence
  4. Efficient Evolutionary Search Over Chemical Space with Large Language Models
    2024/06/23 by Haorui Wang, Wang, Haorui, Marta Skreta +24 · 10 citations
    Computer Science · Biochemistry, Genetics and Molecular Biology · #Evolutionary Algorithms and Applications #Metaheuristic Optimization Algorithms Research #DNA and Biological Computing
  5. Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
    2024/10/10 by Yuanqi Du, Du, Yuanqi, Michael Plainer +13 · 1 voice · 10 citations
    Decision Sciences · #Probabilistic and Robust Engineering Design
  6. A Computational Framework for Solving Wasserstein Lagrangian Flows
    2023/10/16 by Kirill Neklyudov, Rob Brekelmans, Neklyudov, Kirill +9 · 7 citations
    Physics and Astronomy · Engineering · Computer Science · #Model Reduction and Neural Networks #Lattice Boltzmann Simulation Studies #Generative Adversarial Networks and Image Synthesis
  7. Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold
    2024/08/26 by Atanackovic, Lazar, Zhang, Xi, Amos, Brandon +5 · 8 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  8. Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
    2024/02/28 by Kong, Lingkai, Du, Yuanqi, Mu, Wenhao +8 · 6 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  9. Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation
    2023/07/06 by Neklyudov, Kirill, Nys, Jannes, Thiede, Luca +4 · 3 citations
    #Chemical Physics (physics.chem-ph) #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG)
  10. Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities
    2025/06/19 by Akhound-Sadegh, Tara, Lee, Jungyoon, Bose, Avishek Joey +7 · 11 citations
    Materials Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Model Reduction and Neural Networks #Quantum many-body systems
  11. Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition
    2023/01/19 by Juan Carrasquilla, Carrasquilla, Juan, Mohamed Hibat-Allah +11 · 2 citations
    Computer Science · #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Neural Networks and Reservoir Computing #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph) #Stochastic Gradient Optimization Techniques
  12. Structured Bayesian Pruning via Log-Normal Multiplicative Noise
    2017/05/20 by Neklyudov, Kirill, Molchanov, Dmitry, Ashukha, Arsenii +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (stat.ML)
  13. Variance Networks: When Expectation Does Not Meet Your Expectations
    2018/03/10 by Neklyudov, Kirill, Molchanov, Dmitry, Ashukha, Arsenii +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (stat.ML)
  14. Involutive MCMC: a Unifying Framework
    2020/06/30 by Neklyudov, Kirill, Welling, Max, Egorov, Evgenii +1 · 1 citation
    #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
  15. Amortized Sampling with Transferable Normalizing Flows
    2025/08/25 by Tan, Charlie B., Hassan, Majdi, Klein, Leon +5 · 1 voice · 5 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  16. Particle Dynamics for Learning EBMs
    2021/11/26 by Neklyudov, Kirill, Jaini, Priyank, Welling, Max · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC
    2023/12/09 by Lin Wu, Felix Dangel, Lin, Wu +11 · 1 citation
    Computer Science · Earth and Planetary Sciences · Physics and Astronomy · #FOS: Computer and information sciences #Geophysical and Geoelectrical Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Model Reduction and Neural Networks