Chen, Ricky T. Q.
- Neural Ordinary Differential Equations
2018/06/19 by Ricky T. Q. Chen, Yulia Rubanova, Chen, Ricky T. Q. +5 · 5 voices · 556 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Generative Adversarial Networks and Image Synthesis #Computational Physics and Python Applications
- Flow Matching for Generative Modeling
2022/10/06 by Lipman, Yaron, Chen, Ricky T. Q., Ben-Hamu, Heli +2 · 1107 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Flow Matching Guide and Code
2024/12/09 by Yaron Lipman, Marton Havasi, Lipman, Yaron +18 · 10 voices · 80 citations
Decision Sciences · Computer Science · #Simulation Techniques and Applications #Software System Performance and Reliability
- FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
2018/10/02 by Will Grathwohl, Grathwohl, Will, Ricky T. Q. Chen +7 · 79 citations
Computer Science · Physics and Astronomy · #Generative Adversarial Networks and Image Synthesis #Model Reduction and Neural Networks #Computational Physics and Python Applications
- Multisample Flow Matching: Straightening Flows with Minibatch Couplings
2023/04/28 by Aram-Alexandre Pooladian, Heli Ben-Hamu, Pooladian, Aram-Alexandre +9 · 1 voice · 39 citations
#cs.LG
- Discrete Flow Matching
2024/07/22 by Gat, Itai, Remez, Tal, Shaul, Neta +5 · 71 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Scalable Gradients for Stochastic Differential Equations
2020/01/05 by Li, Xuechen, Wong, Ting-Kam Leonard, Chen, Ricky T. Q. +1 · 27 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA)
- HMSPC: A Hybrid Mechanistic-Stochastic Physical-Continuous Model for Battery Dynamics
2019/07/08 by Yulia Rubanova, Ricky T. Q. Chen, Rubanova, Yulia +3 · 29 citations
Computer Science · Decision Sciences · Engineering · #Time Series Analysis and Forecasting #Stock Market Forecasting Methods #Energy Load and Power Forecasting
- Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
2024/09/13 by Carles Domingo-Enrich, Michal Drozdzal, Domingo-Enrich, Carles +5 · 50 citations
Mathematics · Economics, Econometrics and Finance · #Markov Chains and Monte Carlo Methods #Stochastic processes and financial applications
- Residual Flows for Invertible Generative Modeling
2019/06/06 by Chen, Ricky T. Q., Behrmann, Jens, Duvenaud, David +1 · 12 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Guided Flows for Generative Modeling and Decision Making
2023/11/22 by Qinqing Zheng, Zheng, Qinqing, Matt Le +9 · 22 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Music and Audio Processing #Reinforcement Learning in Robotics #Robotics (cs.RO) #Topic Modeling
- Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
2025/04/16 by Aaron Havens, Aaron M. Havens, Havens, Aaron +26 · 2 voices · 27 citations
Materials Science · Computer Science · #Machine Learning in Materials Science #Advanced Graph Neural Networks #Gaussian Processes and Bayesian Inference
- Theseus: A Library for Differentiable Nonlinear Optimization
2022/07/19 by Luis Villaseñor-Pineda, Taosha Fan, Pineda, Luis +23 · 11 citations
Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Robotics (cs.RO) #Sparse and Compressive Sensing Techniques
- Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective
2024/12/04 by Neta Shaul, Itai Gat, Shaul, Neta +15 · 1 voice · 17 citations
Engineering · #Fluid Dynamics and Turbulent Flows #Lattice Boltzmann Simulation Studies
- Generator Matching: Generative modeling with arbitrary Markov processes
2024/10/27 by Peter Holderrieth, Marton Havasi, Holderrieth, Peter +15 · 16 citations
Engineering · #Electric Power System Optimization
- Matching Normalizing Flows and Probability Paths on Manifolds
2022/07/11 by Ben-Hamu, Heli, Cohen, Samuel, Bose, Joey +5 · 7 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Stochastic Optimal Control Matching
2023/12/04 by Carles Domingo-Enrich, Domingo-Enrich, Carles, Jiequn Han +7 · 10 citations
Computer Science · Mathematics · Physics and Astronomy · #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks
- Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
2020/12/10 by Chin-Wei Huang, Ricky T. Q. Chen, Huang, Chin-Wei +5 · 6 citations
Computer Science · #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
- Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
2023/10/04 by Dinghuai Zhang, Ricky T. Q. Chen, Zhang, Dinghuai +7 · 7 citations
Computer Science · #Generative Adversarial Networks and Image Synthesis #Music and Audio Processing #Gaussian Processes and Bayesian Inference
- "Hey, that's not an ODE": Faster ODE Adjoints via Seminorms
2020/09/20 by Kidger, Patrick, Chen, Ricky T. Q., Lyons, Terry · 3 citations
#Classical Analysis and ODEs (math.CA) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG)
- Edit Flows: Flow Matching with Edit Operations
2025/06/10 by Havasi, Marton, Karrer, Brian, Gat, Itai +1 · 18 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
2021/02/12 by Xu, Winnie, Chen, Ricky T. Q., Li, Xuechen +1 · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Bespoke Solvers for Generative Flow Models
2023/10/29 by Neta Shaul, Shaul, Neta, Juan C. Pérez +9 · 5 citations
Computer Science · #Generative Adversarial Networks and Image Synthesis #Machine Learning in Healthcare #Explainable Artificial Intelligence (XAI)
- On Kinetic Optimal Probability Paths for Generative Models
2023/06/11 by Neta Shaul, Ricky T. Q. Chen, Shaul, Neta +7 · 4 citations
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
- FlowDec: A flow-based full-band general audio codec with high perceptual quality
2025/03/03 by Simon Welker, Welker, Simon, Matthew Le +11 · 9 citations
Computer Science · Engineering · #Advanced Data Compression Techniques #Speech and Audio Processing #Advanced Adaptive Filtering Techniques
- Generalized Schrödinger Bridge Matching
2023/10/03 by Guan-Horng Liu, Liu, Guan-Horng, Yaron Lipman +9 · 2 citations
Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC)
- Isolating Sources of Disentanglement in Variational Autoencoders
2018/02/14 by Chen, Ricky T. Q., Li, Xuechen, Grosse, Roger +1 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- TaskMet: Task-Driven Metric Learning for Model Learning
2023/12/08 by Dishank Bansal, Ricky T. Q. Chen, Bansal, Dishank +5 · 2 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning #Machine Learning and Data Classification
- Neural Networks with Cheap Differential Operators
2019/12/08 by Chen, Ricky T. Q., Duvenaud, David · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models
2020/04/01 by Luo, Yucen, Beatson, Alex, Norouzi, Mohammad +4 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Latent State Marginalization as a Low-cost Approach for Improving Exploration
2022/10/03 by Dinghuai Zhang, Aaron Courville, Zhang, Dinghuai +9 · 2 citations
Computer Science · #Reinforcement Learning in Robotics #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning
- Adjoint Schrödinger Bridge Sampler
2025/06/27 by Guan-Horng Liu, Liu, Guan-Horng, Jaemoo Choi +7 · 1 voice · 4 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #cs.LG #math.OC #stat.ML
- Reflected Schrödinger Bridge for Constrained Generative Modeling
2024/01/06 by Deng, Wei, Chen, Yu, Yang, Nicole Tianjiao +3 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Distributional GFlowNets with Quantile Flows
2023/02/11 by Dinghuai Zhang, Zhang, Dinghuai, Ling Pan +7 · 1 citation
Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Computation (stat.CO) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
- Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
2024/03/02 by Shaul, Neta, Singer, Uriel, Chen, Ricky T. Q. +4 · 1 citation
#Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Neural Optimal Transport with Lagrangian Costs
2024/06/01 by Pooladian, Aram-Alexandre, Domingo-Enrich, Carles, Chen, Ricky T. Q. +1 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Variational Schrödinger Diffusion Models
2024/05/08 by Wei Deng, Deng, Wei, Weijian Luo +10 · 1 citation
Engineering · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Numerical methods in inverse problems #Thermoelastic and Magnetoelastic Phenomena
- OneFlow: Concurrent Mixed-Modal and Interleaved Generation with Edit Flows
2025/10/03 by Nguyen, John, Havasi, Marton, Berrada, Tariq +2 · 5 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences