Alexander Tong
18 papers · 2020–2025 · 4 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+8 more ↓ Show less ↑
π Renaissance Researcher (6) π Interdisciplinary Bridge π Conference Polyglot (4) π Academic Marathon (5) πΊοΈ Taxonomy Completionist (17)
πΊοΈ
Taxonomy Completionist
(17)
π
Cross-Pollinator
(15)
π₯
Mega-Team
(22)
π
Triple Crown
π
Keyword Champion
(2)
β‘
Prolific Year
(6)
π
Century Club
(18)
π₯
Unstoppable
(6)
Conferences
ICML (6)
NIPS (6)
ICLR (5)
JMLR (1)
Top co-authors
Keywords
flow matching
(3)
manifold learning
(3)
optimal transport
(3)
trajectory inference
(2)
geodesic distance
(2)
riemannian geometry
(1)
causal discovery
(1)
dimensionality reduction
(1)
reinforcement learning from human feedback
(1)
generative flow network
(1)
time series modeling
(1)
protein design
(1)
bayesian inference
(1)
trajectory modeling
(1)
sinkhorn algorithm
(1)
riemannian metric
(1)
generative model
(1)
neural ordinary differential equation
(1)
point cloud
(1)
unsupervised learning
(1)
Papers
Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
ICML 2025
The Superposition of Diffusion Models Using the ItΓ΄ Density Estimator
ICLR 2025
Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen
ICLR 2025
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold
ICLR 2025
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction
ICLR 2025
Scalable Equilibrium Sampling with Sequential Boltzmann Generators
ICML 2025
SE(3)-Stochastic Flow Matching for Protein Backbone Generation
ICLR 2024
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
ICML 2024
A Computational Framework for Solving Wasserstein Lagrangian Flows
ICML 2024
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation
NIPS 2024
Trajectory Flow Matching with Applications to Clinical Time Series Modelling
NIPS 2024
Metric Flow Matching for Smooth Interpolations on the Data Manifold
NIPS 2024
Neural FIM for learning Fisher information metrics from point cloud data
ICML 2023
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction
NIPS 2023
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
NIPS 2023
Manifold Interpolating Optimal-Transport Flows for Trajectory Inference
NIPS 2022
POT: Python Optimal Transport
JMLR 2021
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
ICML 2020