Alexander Tong

Publications

• Hacking Generative Perplexity: Why Unconditional Text Evaluation Needs Distributional Metrics

  Antonio Franca, Alexander Tong

  In ICML 2026 Workshop on Structured Probabilistic Inference & Generative Modeling (SPIGM)

  July 2026

• Why Are DMD Students Lazy? Understanding the Copying Behavior in Few-Step Distillation

  Shucheng Li, Iolo Jones, Alexander Tong^†, Michael M. Bronstein^†

  In ICML 2026 Workshop on High-dimensional Learning Dynamics

  July 2026

• MacroGuide: Topological Guidance for Macrocycle Generation

  Alicja Maksymiuk, Alexandre Duplessis, Michael Bronstein, Alexander Tong, Fernanda Duarte, İsmail İlkan Ceylan

  In ICML 2026

  July 2026

• Strong Stochastic Flow Maps

  Sam McCallum^*, Zander W. Blasingame^*, Timothy Herschell, Niklas Rindtorff, Alexander Tong^†, James Foster^†

  In ICML 2026 Workshop on Structured Probabilistic Inference & Generative Modeling (SPIGM)

  July 2026

• Autoregressive Boltzmann Generators

  Danyal Rehman, Charlie B. Tan, Yoshua Bengio, Joey Bose, Alexander Tong

  In ICML 2026 (Spotlight)

  July 2026

• Beta cell-derived cholecystokinin drives obesity-associated pancreatic adenocarcinoma development

  Cathy C. Garcia^*, Aarthi Venkat^*, Daniel C. McQuaid^*, Sherry S. Agabiti, Alexander Tong, Boby Mathew, Rebecca L. Cardone, Rebecca Starble, Christian F. Ruiz, Christy Zheng, Akin Sogunro, Jeremy B. Jacox, Ken H. Loh, Richard G. Kibbey, Smita Krishnaswamy^†, Mandar Deepak Muzumdar^†

  In Nature Communications

  June 2026

• Entropy Across the Bridge: Conditional-Marginal Discretization for Flow and Schrödinger Samplers

  Bruno Trentini, Dejan Stancevic, Michael M. Bronstein, Alexander Tong, Luca Ambrogioni

  Preprint

  May 2026

• Coupling Models for One-Step Discrete Generation

  Fred Zhangzhi Peng, Avishek Joey Bose, Anru R. Zhang, Alexander Tong

  Preprint

  May 2026

• Don't Retrain, Align: Adapting Autoregressive LMs to Diffusion LMs via Representation Alignment

  Fred Zhangzhi Peng, Alexis Fox, Anru R. Zhang, Alexander Tong

  Preprint

  May 2026

• FALCON: Few-step Accurate Likelihoods for Continuous Flows

  Danyal Rehman, Tara Akhound-Sadegh, Artem Gazizov, Yoshua Bengio, Alexander Tong

  In ICLR 2026 (Oral)

  May 2026

• OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction

  Emily Jin^*, Andrei Cristian Nica^*, Mikhail Galkin, Jarrid Rector-Brooks, Kin Long Kelvin Lee, Santiago Miret, Frances H. Arnold, Michael Bronstein, Avishek Joey Bose, Alexander Tong, Chenghao Liu

  In ICLR 2026

  May 2026

• Planner Aware Path Learning in Diffusion Language Models Training

  Fred Zhangzhi Peng^*, Zachary Bezemek^*, Jarrid Rector-Brooks, Shuibai Zhang, Anru R. Zhang, Michael Bronstein, Avishek Joey Bose^†, Alexander Tong^†

  In ICLR 2026 (Oral)

  May 2026

• Topological Flow Matching

  Kacper Wyrwal, Ismail Ilkan Ceylan, Alexander Tong

  In ICLR 2026

  May 2026

• Branched Schrödinger Bridge Matching

  Sophia Tang, Yinuo Zhang, Alexander Tong, Pranam Chatterjee

  In ICLR 2026

  May 2026

• Flow matching for generative modelling in bioinformatics and computational biology

  Alex Morehead^*, Lazar Atanackovic^*, Akshata Hegde^*, Yanli Wang^*, Frimpong Boadu^*, Joel Selvaraj^*, Alexander Tong, Aditi Krishnapriyan, Jianlin Cheng

  In Nature Machine Intelligence

  April 2026

• General Multimodal Protein Design Enables DNA-Encoding of Chemistry

  Jarrid Rector-Brooks^*, Théophile Lambert^*, Marta Skreta^*, Daniel Roth^*, Yueming Long, Zi-Qi Li, Xi Zhang, Miruna Cretu, Francesca-Zhoufan Li, Tanvi Ganapathy, Emily Jin, Avishek Joey Bose, Jason Yang, Kirill Neklyudov, Yoshua Bengio, Alexander Tong, Frances H. Arnold, Cheng-Hao Liu

  Preprint

  April 2026

• MIOFlow 2.0: A Unified Framework for Inferring Cellular Stochastic Dynamics from Single Cell and Spatial Transcriptomics Data

  Xingzhi Sun, João Felipe Rocha, Brett Phelan, Dhananjay Bhaskar, Guillaume Huguet, Yanlei Zhang, Alexander Tong, Ke Xu, Oluwadamilola Fasina, Mark Gerstein, Natalia Ivanova, Christine L. Chaffer, Guy Wolf, Smita Krishnaswamy

  Preprint

  March 2026

• Amortized Sampling with Transferable Normalizing Flows

  Charlie B. Tan^*, Majdi Hassan^*, Leon Klein, Saifuddin Syed, Dominique Beaini, Michael M. Bronstein, Alexander Tong^†, Kirill Neklyudov^†

  In NeurIPS 2025

  December 2025

• Curly Flow Matching for Learning Non-gradient Field Dynamics

  Katarina Petrović, Lazar Atanackovic, Viggo Moro, Kacper Kapuśniak, İsmail İlkan Ceylan, Michael Bronstein, Avishek Joey Bose^†, Alexander Tong^†

  In NeurIPS 2025

  December 2025

• Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities

  Tara Akhound-Sadegh^*, Jungyoon Lee^*, Avishek Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov^†, Alexander Tong^†

  In NeurIPS (spotlight)

  December 2025

• Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction

  Vincent Pauline, Tobias Höppe, Kirill Neklyudov, Alexander Tong, Stefan Bauer, Andrea Dittadi

  arXiv preprint

  December 2025

• FORT: Forward-Only Regression Training of Normalizing Flows

  Danyal Rehman, Oscar Davis, Jiarui Lu, Jian Tang, Michael Bronstein, Yoshua Bengio, Alexander Tong^†, Avishek Joey Bose^†

  ICML GenBio Best Paper Award 2025

  July 2025

• Scalable Equilibrium Sampling with Sequential Boltzmann Generators

  Charlie B. Tan^*, Avishek Joey Bose^*, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong

  In ICML 2025

  July 2025

• Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts

  Marta Skreta^*, Tara Akhound-Sadegh^*, Viktor Ohanesian^*, Roberto Bondesan, Alán Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong^†, Kirill Neklyudov^†

  In ICML 2025 (spotlight)

  July 2025

• Defining and Benchmarking Open Problems in Single-Cell Analysis

  Malte Luecken^*, Scott Gigante^*, Daniel Burkhardt^*, Robrecht Cannoodt, Daniel Strobl, Nikolay Markov, Luke Zappia, Giovanni Palla, Wesley Lewis, Daniel Dimitrov, Michael Vinyard, Daniel Magruder, Alma Andersson, Emma Dann, Qian Qin, Dominik Otto, Michal Klein, Olga Botvinnik, Louise Deconinck, Kai Waldrant, Bastian Rieck, Constantin Ahlmann-Eltze, Eduardo Da Veiga Beltrame, Andrew Benz, Carmen Bravo González-Blas, Ann Chen, Benjamin DeMeo, Can Ergen, Swann Floc'hlay, Adam Gayoso, Stephanie Hicks, Yuge Ji, Vitalii Kleshchevnikov, Gioele La Manno, Maximilian Lombardo, Romain Lopez, Dario Righelli, Hirak Sarkar, Valentine Svensson, Alexander Tong, Galen Xing, Chenling Xu, Jonathan Bloom, Angela Pisco, Julio Saez-Rodriguez, Drausin Wulsin, Luca Pinello, Yvan Saeys, Fabian Theis, Smita Krishnaswamy

  In Nature Biotechnology, 2025

  June 2025

• Generating Multi-Modal and Multi-Attribute Single-Cell Counts with CFGen

  Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian Theis

  In ICLR 2025

  May 2025

• Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction

  Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Zachary Quinn, Chenghao Liu, Sarthak Mittal, Nouha Dziri, Michael Bronstein, Yoshua Bengio, Pranam Chatterjee, Alexander Tong^†, Avishek Joey Bose^†

  In ICLR 2025

  May 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

  In ICLR 2025

  May 2025

• The Superposition of Diffusion Models Using the Itô Density Estimator

  Marta Skreta^*, Lazar Atanackovic^*, Avishek Joey Bose, Alexander Tong, Kirill Neklyudov

  In ICLR 2025 (spotlight)

  May 2025

• geneRNIB: a living benchmark for gene regulatory network inference

  Jalil Nourisa, Antoine Passemiers, Marco Stock, Berit Zeller-Plumhoff, Robrecht Cannoodt, Christian Arnold, Alexander Tong, Jason Hartford, Antonio Scialdone, Yves Moreau, Yang Li, Malte D. Luecken

  In bioRxiv

  April 2025

• Hidden sampling biases inflate performance in gene regulatory network inference

  Marco Stock^*, Florin Ratajczak^*, Paul Bertin, Eva Hoermanseder, Yoshua Bengio, Jason Hartford, Pascal Falter-Braun, Matthias Heinig, Alexander Tong, Antonio Scialdone

  Preprint (bioRxiv)

  April 2025

• Path Planning for Masked Diffusion Model Sampling

  Fred Zhangzhi Peng^*, Zachary Bezemek^*, Sawan Patel, Jarrid Rector-Brooks, Sherwood Yao, Alexander Tong^†, Pranam Chatterjee^†

  arXiv preprint

  February 2025

• Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone 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^†

  In NeurIPS 2024

  December 2024

• Metric Flow Matching for Smooth Interpolations on the Data Manifold

  Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael Bronstein, Avishek Joey Bose, Francesco Di Giovanni

  In NeurIPS 2024

  December 2024

• A Computational Framework for Solving Wasserstein Lagrangian Flows

  Kirill Neklyudov^*, Rob Brekelmans^*, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani

  In ICML 2024

  July 2024

• Iterated Denoising Energy Matching for Sampling from Boltzmann Densities

  Tara Akhound-Sadegh^*, Jarrid Rector-Brooks^*, Avishek Joey Bose^*, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong

  In ICML 2024

  July 2024

• Learnable Filters for Geometric Scattering Modules

  Alexander Tong^*, Frederik Wenkel^*, Dhananjay Bhaskar, Kincaid Macdonald, Jackson Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf

  In IEEE Transactions on Signal Processing

  June 2024

• SE(3)-Stochastic Flow Matching for Protein Backbone Generation

  Avishek Joey Bose^*, Tara Akhound-Sadegh^*, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael Bronstein, Alexander Tong

  In ICLR 2024 (Spotlight)

  May 2024

• 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

  In Transactions on Machine Learning Research (TMLR), 2024

  May 2024

• A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction

  Guillaume Huguet^*, Alexander Tong^*, Edward De Brouwer^*, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy

  In NeurIPS

  December 2023

• DynGFN: Bayesian Dynamic Causal Discovery Using Generative Flow Networks

  Lazar Atanackovic^*, Alexander Tong^*, Jason Hartford, Leo J. Lee, Bo Wang, Yoshua Bengio

  In NeurIPS. Also presented at Frontiers4LCD Workshop @ NeurIPS 2022

  December 2023

• Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems

  Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio^†, Dianbo Liu^†

  In arXiv

  October 2023

• Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds

  Guillaume Huguet^*, Alexander Tong^*, María Ramos Zapatero, Christpher J. Tape, Guy Wolf, Smita Krishnaswamy

  In IEEE MLSP

  September 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

  In ICML

  July 2023

• Graph Fourier MMD for signals on data graphs

  Sam Leone, Alexander Tong, Guillaume Huguet, Guy Wolf, Smita Krishnaswamy

  In SAMPTA

  July 2023

• Single-Cell Analysis Reveals Inflammatory Interactions Driving Macular Degeneration

  Manik Kuchroo^*, Marcello DiStasio^*, Eric Song^*, Eda Calapkulu, Le Zhang, Maryam Ige, Amar H. Sheth, Abdelilah Majdoubi, Madhvi Menon, Alexander Tong, Abhinav Godavarthi, Yu Xing, Scott Gigante, Holly Steach, Jessie Huang, Guillaume Huguet, Janhavi Narain, Kisung You, George Mourgkos, Rahul M. Dhodapkar, Matthew J. Hirn, Bastian Rieck, Guy Wolf, Smita Krishnaswamy^†, Brian P. Hafler^†

  In Nature Communications

  June 2023

• Trellis tree-based analysis reveals stromal regulation of patient-derived organoid drug responses

  María Ramos Zapatero^*, Alexander Tong^*, Jahangir Sufi, Petra Vlckova, Ferran Cardoso Rodriguez, Callum Nattress, Xiao Qin, Daniel Hochhauser, Smita Krishnaswamy, Christopher J. Tape

  In Cell

  June 2023

• Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms

  Michael Perlmutter, Alexander Tong, Feng Gao, Guy Wolf, Matthew Hirn

  In SIAM Journal on Mathematics of Data Science (SIMODS), 2023

  May 2023

• Learning Transcriptional and Regulatory Dynamics Driving Cancer Cell Plasticity Using Neural ODE-Based Optimal Transport

  Alexander Tong^*, Manik Kuchroo^*, Shabarni Gupta, Aarthi Venkat, Beatriz P. San Juan, Laura Rangel, Brandon Zhu, John G. Lock, Christine L. Chaffer, Smita Krishnaswamy

  In BioRxiv

  April 2023

• Manifold Interpolating Optimal-Transport Flows for Trajectory Inference

  Guillaume Huguet^*, D. S. Magruder^*, Alexander Tong^*, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy

  In NeurIPS

  December 2022

• Immune Cells and Their Inflammatory Mediators Modify Beta Cells and Cause Checkpoint Inhibitor-Induced Diabetes

  Ana Luisa Perdigoto, Songyan Deng, Katherine C. Du, Manik Kuchroo, Daniel B. Burkhardt, Alexander Tong, Gary Israel, Marie E. Robert, Stuart P. Weisberg, Nancy Kirkiles-Smith, Angeliki M. Stamatouli, Harriet M. Kluger, Zoe Quandt, Arabella Young, Mei-Ling Yang, Mark J. Mamula, Jordan S. Pober, Mark S. Anderson, Smita Krishnaswamy, Kevan C. Herold

  In JCI Insight 7(17), e156330, 2022

  June 2022

• Multiscale PHATE identifies multimodal signatures of COVID-19

  Manik Kuchroo^*, Jessie Huang^*, Patrick Wong^*, Jean-Christophe Grenier, Dennis Shung, Alexander Tong, Carolina Lucas, Jon Klein, Daniel Burkhardt, Scott Gigante, Abhinav Godavarthi, Benjamin Israelow, Tianyang Mao, Ji Eun Oh, Julio Silva, Takehiro Takahashi, Camila D. Odio, Arnau Casanovas-Massana, John Fournier, Yale IMPACT Team, Shelli Farhadian, Charles S. Dela Cruz, Albert I. Ko, F. Perry Wilson, Julie Hussin^†, Guy Wolf^†, Akiko Iwasaki^†, Smita Krishnaswamy^†

  In Nature Biotechnology

  June 2022

• Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance

  Alexander Tong, Guillaume Huguet, Dennis Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy

  In ICASSP

  May 2022

• A sandbox for prediction and integration of DNA, RNA, and protein data in single cells

  Malte D Luecken, Daniel B Burkhardt, Robrecht Cannoodt, Christopher Lance, Aditi Agrawal, Hananeh Aliee, Ann T Chen, Louise Deconinck, Angela M Detweiler, Alejandro Granados, Shelly Huynh, Laura Isacco, Yang Joon Kim, Sunil Kuppasani, Heiko Lickert, Aaron McGeever, Honey Mekonen, Joaquin Caceres, Maurizio Morri, Michaela Mueller, Norma F Neff, Sheryl Paul, Kaylie Schneider, Scott Steelman, Michael Sterr, Dan J Treacy, Alexander Tong, Alexandra-Chloé Villani, Guilin Wang, Jia Yan, Ce Zhang, Angela O Pisco, Smita Krishnaswamy, Fabian J Theis, Jonathan M Bloom

  In NeurIPS Datasets and Benchmarks

  December 2021

• MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data

  Michal Gerasimiuk^*, Dennis L. Shung^*, Alexander Tong, Adrian J. Stanley, Machael Shultz, Jeffrey Ngu, Loren Laine, Guy Wolf, Smita Krishnaswamy

  In IEEE Big Data

  December 2021

• Multimodal data visualization and denoising with integrated diffusion

  Manik Kuchroo^*, Abhinav Godavarthi^*, Alexander Tong, Smita Krishnaswamy, Guy Wolf

  In IEEE MLSP

  September 2021

• Data-Driven Learning of Geometric Scattering Networks

  Alexander Tong^*, Frederik Wenkel^*, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf

  In IEEE MLSP. Also presented at ML4M Workshop @ NeurIPS 2020

  September 2021

• Diffusion Earth Mover's Distance and Distribution Embeddings

  Alexander Tong^*, Guillaume Huguet^*, Amine Natik^*, Kincaid MacDonald, Manik Kuchroo, Ronald Coifman, Guy Wolf, Smita Krishnaswamy

  In ICML. Also presented at LMRL Workshop @ NeurIPS 2020

  July 2021

• Quantifying the effect of experimental perturbations in single-cell RNA-sequencing data using graph signal processing

  Daniel B. Burkhardt^*, Jay S. Stanley^*, Alexander Tong, Ana Luisa Perdigoto, Scott A. Gigante, Kevan C. Herold, Guy Wolf, Antonio J. Giraldez, David van Dijk, Smita Krishnaswamy

  In Nature Biotechnology

  June 2021

• POT: Python Optimal Transport

  Remi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z Alaya, Aurelie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Leo 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

  In JMLR

  June 2021

• Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators

  Alexander Tong, Guy Wolf, Smita Krishnaswamy

  Journal version in Journal of Signal Processing Systems (2021). Presented at IEEE MLSP 2020 (*Best Student Paper Award*).

  June 2021

• Abstract 2839: Understanding the mesenchymal-to-epithelial transition and its drivers in triple-negative breast cancer with continuous normalizing flows

  Alexander Tong, Beatriz P. San Juan, Brandon Zhu, Christine L. Chaffer, Smita Krishnaswamy

  AACR

  April 2021

• Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings

  Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf^†, Smita Krishnaswamy^†

  In IEEE Big Data. Also at GRLB Workshop @ ICML 2020

  December 2020

• Interpretable Neuron Structuring with Graph Spectral Regularization

  Alexander Tong^*, David van Dijk^*, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy

  In IDA Also presented at RLGM Workshop @ ICLR 2019

  October 2020

• TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics

  Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy

  In ICML. Also at LMRL Workshop @ NeurIPS 2019

  July 2020

• Interpolating Optimal Transport Barycenters of Patient Manifolds

  Alexander Tong, Smita Krishnaswamy

  In ISMB

  July 2020

• Finding Archetypal Spaces Using Neural Networks

  David van Dijk^*, Daniel B. Burkhardt^*, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy

  In IEEE Big Data

  December 2019

• Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators

  Alexander Tong, Guy Wolf, Smita Krishnaswamy

  In Journal of Signal Processing Systems

  May 2019

• Allocate-On-Use Space Complexity of Shared-Memory Algorithms

  James Aspnes, Bernhard Haeupler, Alexander Tong, Philipp Woelfel

  In DISC

  October 2018