Ricky T. Q. Chen
41 papers · 2018–2026 · 6 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (37) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
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Deep Specialist
(16)
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Dynamic Duo
(12)
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Triple Crown
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Keyword Champion
(6)
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Keyword Pioneer
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Trend Setter
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Prolific Year · Prolific
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Keyword Collector
(159)
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Unstoppable · Bronze
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Century Club · Bronze
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Renaissance Researcher
(5)
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Research topics
Machine Learning
(33)
Deep Learning
(32)
Optimization & Theory
(28)
Models
(26)
Architectures
(8)
Artificial Intelligence
(7)
Core Methods
(7)
Computer Vision
(4)
Mathematics & Optimization
(4)
Core AI
(4)
Generation
(4)
Optimization
(4)
Bayesian & Probabilistic · Artificial Intelligence
(3)
Learning Types
(3)
Bayesian & Probabilistic · Machine Learning
(2)
Keywords
flow matching
(9)
generative model
(7)
generative modeling
(6)
diffusion model
(5)
normalizing flow
(5)
optimal transport
(5)
neural network
(5)
density estimation
(4)
ordinary differential equation
(4)
probability path
(4)
continuous normalizing flow
(4)
stochastic optimal control
(4)
stochastic differential equation
(3)
riemannian flow matching
(3)
variational inference
(3)
stochastic process
(3)
vector field
(3)
variational autoencoder
(2)
maximum likelihood
(2)
neural ordinary differential equation
(2)
Papers
Flowception: Temporally Expansive Flow Matching for Video Generation
CVPR 2026
Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
ICLR 2025
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
ICML 2025
FlowDec: A flow-based full-band general audio codec with high perceptual quality
ICLR 2025
Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective
ICLR 2025
Generator Matching: Generative modeling with arbitrary Markov processes
ICLR 2025
Simulation-Free Differential Dynamics Through Neural Conservation Laws
UAI 2025
Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
ICML 2024
Bespoke Solvers for Generative Flow Models
ICLR 2024
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
ICLR 2024
Discrete Flow Matching
NeurIPS 2024
FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
NeurIPS 2024
Flow Matching on General Geometries
ICLR 2024
FlowMM: Generating Materials with Riemannian Flow Matching
ICML 2024
Generalized Schrödinger Bridge Matching
ICLR 2024
Neural Optimal Transport with Lagrangian Costs
UAI 2024
Stochastic Optimal Control Matching
NeurIPS 2024
Variational Schrödinger Diffusion Models
ICML 2024
Flow Matching for Generative Modeling
ICLR 2023
Latent State Marginalization as a Low-cost Approach for Improving Exploration
ICLR 2023
Multisample Flow Matching: Straightening Flows with Minibatch Couplings
ICML 2023
On Kinetic Optimal Probability Paths for Generative Models
ICML 2023
TaskMet: Task-driven Metric Learning for Model Learning
NeurIPS 2023
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
AISTATS 2022
Matching Normalizing Flows and Probability Paths on Manifolds
ICML 2022
Neural Conservation Laws: A Divergence-Free Perspective
NeurIPS 2022
Semi-Discrete Normalizing Flows through Differentiable Tessellation
NeurIPS 2022
Theseus: A Library for Differentiable Nonlinear Optimization
NeurIPS 2022
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
ICLR 2021
"Hey, that’s not an ODE": Faster ODE Adjoints via Seminorms
ICML 2021
Learning Neural Event Functions for Ordinary Differential Equations
ICLR 2021
Neural Spatio-Temporal Point Processes
ICLR 2021
Scalable Gradients for Stochastic Differential Equations
AISTATS 2020
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models
ICLR 2020
FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models
ICLR 2019
Invertible Residual Networks
ICML 2019
Latent Ordinary Differential Equations for Irregularly-Sampled Time Series
NeurIPS 2019
Neural Networks with Cheap Differential Operators
NeurIPS 2019
Residual Flows for Invertible Generative Modeling
NeurIPS 2019
Isolating Sources of Disentanglement in Variational Autoencoders
NeurIPS 2018
Neural Ordinary Differential Equations
NeurIPS 2018