Tong, Alexander

37 publications

NeurIPS 2025 Amortized Sampling with Transferable Normalizing Flows Charlie B. Tan, Majdi Hassan, Leon Klein, Saifuddin Syed, Dominique Beaini, Michael M. Bronstein, Alexander Tong, Kirill Neklyudov

NeurIPS 2025 Curly Flow Matching for Learning Non-Gradient Field Dynamics Katarina Petrović, Lazar Atanackovic, Viggo Moro, Kacper Kapuśniak, Ismail Ilkan Ceylan, Michael M. Bronstein, Joey Bose, Alexander Tong

ICLRW 2025 Curly Flow Matching for Learning Non-Gradient Field Dynamics Katarina Petrović, Lazar Atanackovic, Kacper Kapuśniak, Michael M. Bronstein, Joey Bose, Alexander Tong

ICLRW 2025 Curly Flow Matching for Learning Non-Gradient Field Dynamics Katarina Petrović, Lazar Atanackovic, Kacper Kapusniak, Michael M. Bronstein, Joey Bose, Alexander Tong

ICML 2025 Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian, Roberto Bondesan, Alan Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong, Kirill Neklyudov

ICLRW 2025 Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian, Roberto Bondesan, Alan Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong, Kirill Neklyudov

ICLRW 2025 Gumbel-SoftMax Score and Flow Matching for Discrete Biological Sequence Generation Sophia Tang, Yinuo Zhang, Alexander Tong, Pranam Chatterjee

ICLR 2025 Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov

ICLR 2025 Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J Theis

ICLRW 2025 Path Planning for Masked Diffusion Models with Applications to Biological Sequence Generation Fred Zhangzhi Peng, Zachary Bezemek, Sawan Patel, Jarrid Rector-Brooks, Sherwood Yao, Alexander Tong, Pranam Chatterjee

NeurIPS 2025 Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jungyoon Lee, Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov, Alexander Tong

ICLRW 2025 SOAPI: Siamese-Guided Generation of Off-Target-Avoiding Protein Interactions Sophia Vincoff, Oscar Davis, Alexander Tong, Joey Bose, Pranam Chatterjee

ICML 2025 Scalable Equilibrium Sampling with Sequential Boltzmann Generators Charlie B. Tan, Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong

ICLRW 2025 Scalable Equilibrium Sampling with Sequential Boltzmann Generators Charlie B. Tan, Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong

ICLRW 2025 Simulation-Free Structure Learning for Stochastic Dynamics Noah El Rimawi-Fine, Adam Stecklov, Lucas Nelson, Alexander Tong, Mathieu Blanchette, Stephen Y. Zhang, Lazar Atanackovic

ICLR 2025 Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Pranam Chatterjee, Alexander Tong, Joey Bose

ICLR 2025 The Superposition of Diffusion Models Using the Itô Density Estimator Marta Skreta, Lazar Atanackovic, Joey Bose, Alexander Tong, Kirill Neklyudov

ICML 2024 A Computational Framework for Solving Wasserstein Lagrangian Flows Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani

TMLR 2024 Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio

ICML 2024 Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jarrid Rector-Brooks, Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong

ICMLW 2024 Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov

NeurIPS 2024 Metric Flow Matching for Smooth Interpolations on the Data Manifold Kacper Kapuśniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael Bronstein, Avishek Joey Bose, Francesco Di Giovanni

ICLR 2024 SE(3)-Stochastic Flow Matching for Protein Backbone Generation Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian Fatras, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong

NeurIPS 2024 Sequence-Augmented SE(3)-Flow Matching for Conditional Protein Generation Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael Bronstein, Alexander Tong, Avishek Joey Bose

NeurIPS 2024 Trajectory Flow Matching with Applications to Clinical Time Series Modelling Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis L. Shung, Alexander Tong

NeurIPSW 2023 A Computational Framework for Solving Wasserstein Lagrangian Flows Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani

NeurIPS 2023 A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy

ICMLW 2023 A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy

NeurIPSW 2023 Causal Discovery in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu

NeurIPS 2023 DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J Lee, Yoshua Bengio, Jason S Hartford

ICMLW 2023 Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio

ICML 2023 Neural FIM for Learning Fisher Information Metrics from Point Cloud Data Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy

ICMLW 2023 Simulation-Free Schrödinger Bridges via Score and Flow Matching Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio

NeurIPSW 2022 Bayesian Dynamic Causal Discovery Alexander Tong, Lazar Atanackovic, Jason Hartford, Yoshua Bengio

NeurIPS 2022 Manifold Interpolating Optimal-Transport Flows for Trajectory Inference Guillaume Huguet, Daniel Sumner Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy

MLOSS 2021 POT: Python Optimal Transport Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T.H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer

ICML 2020 TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics Alexander Tong, Jessie Huang, Guy Wolf, David Van Dijk, Smita Krishnaswamy