Alexander Tong

86 papers A* 18A 2B 1Misc 3Journal 54Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data. CoRR Xingzhi Sun, João F. Rocha, Brett Phelan, Dhananjay Bhaskar, Guillaume Huguet, Yanlei Zhang, Daniel Sumner Magruder, Alexander Tong, Ke Xu, Oluwadamilola Fasina, Mark Gerstein, Guy Wolf, Natalia Ivanova, Christine L. Chaffer, Smita Krishnaswamy
2026	J	`jnl`	MacroGuide: Topological Guidance for Macrocycle Generation. CoRR Alicja Maksymiuk, Alexandre Duplessis, Michael M. Bronstein, Alexander Tong, Fernanda Duarte, Ismail Ilkan Ceylan
2025	J	`jnl`	Amortized Sampling with Transferable Normalizing Flows. CoRR Charlie B. Tan, Majdi Hassan, Leon Klein, Saifuddin Syed, Dominique Beaini, Michael M. Bronstein, Alexander Tong, Kirill Neklyudov
2025	J	`jnl`	Branched Schrödinger Bridge Matching. CoRR Sophia Tang, Yinuo Zhang, Alexander Tong, Pranam Chatterjee
2025	J	`jnl`	Curly Flow Matching for Learning Non-gradient Field Dynamics. CoRR Katarina Petrovic, Lazar Atanackovic, Viggo Moro, Kacper Kapusniak, Ismail Ilkan Ceylan, Michael M. Bronstein, Avishek Joey Bose, Alexander Tong
2025	J	`jnl`	FALCON: Few-step Accurate Likelihoods for Continuous Flows. CoRR Danyal Rehman, Tara Akhound-Sadegh, Artem Gazizov, Yoshua Bengio, Alexander Tong
2025	J	`jnl`	FORT: Forward-Only Regression Training of Normalizing Flows. CoRR Danyal Rehman, Oscar Davis, Jiarui Lu, Jian Tang, Michael M. Bronstein, Yoshua Bengio, Alexander Tong, Avishek Joey Bose
2025	A*	`conf`	Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts. ICML Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian, Roberto Bondesan, Alán Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong, Kirill Neklyudov
2025	J	`jnl`	Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts. CoRR Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian, Roberto Bondesan, Alán Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong, Kirill Neklyudov
2025	J	`jnl`	Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction. CoRR Vincent Pauline, Tobias Höppe, Kirill Neklyudov, Alexander Tong, Stefan Bauer, Andrea Dittadi
2025	J	`jnl`	Gumbel-Softmax Flow Matching with Straight-Through Guidance for Controllable Biological Sequence Generation. CoRR Sophia Tang, Yinuo Zhang, Alexander Tong, Pranam Chatterjee
2025	Misc	`conf`	ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images. ICASSP Chen Liu, Ke Xu, Liangbo L. Shen, Guillaume Huguet, Zilong Wang, Alexander Tong, Danilo Bzdok, Jay Stewart, Jay C. Wang, Luciano V. Del Priore, Smita Krishnaswamy
2025	A*	`conf`	Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold. ICLR Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J. Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov
2025	A*	`conf`	Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen. ICLR Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J. Theis
2025	J	`jnl`	OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction. CoRR Emily Jin, Andrei Cristian Nica, Mikhail Galkin, Jarrid Rector-Brooks, Kin Long Kelvin Lee, Santiago Miret, Frances H. Arnold, Michael M. Bronstein, Avishek Joey Bose, Alexander Tong, Cheng-Hao Liu
2025	J	`jnl`	Path Planning for Masked Diffusion Model Sampling. CoRR Zhangzhi Peng, Zachary Bezemek, Sawan Patel, Jarrid Rector-Brooks, Sherwood Yao, Alexander Tong, Pranam Chatterjee
2025	J	`jnl`	Planner Aware Path Learning in Diffusion Language Models Training. CoRR Fred Zhangzhi Peng, Zachary Bezemek, Jarrid Rector-Brooks, Shuibai Zhang, Anru R. Zhang, Michael M. Bronstein, Avishek Joey Bose, Alexander Tong
2025	J	`jnl`	Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities. CoRR Tara Akhound-Sadegh, Jungyoon Lee, Avishek Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov, Alexander Tong
2025	A*	`conf`	Scalable Equilibrium Sampling with Sequential Boltzmann Generators. ICML Charlie B. Tan, Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong
2025	J	`jnl`	Scalable Equilibrium Sampling with Sequential Boltzmann Generators. CoRR Charlie B. Tan, Avishek Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong
2025	J	`jnl`	Simulation-free Structure Learning for Stochastic Dynamics. CoRR Noah El Rimawi-Fine, Adam Stecklov, Lucas Nelson, Mathieu Blanchette, Alexander Tong, Stephen Y. Zhang, Lazar Atanackovic
2025	A*	`conf`	Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. ICLR Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Pranam Chatterjee, Alexander Tong, Joey Bose
2025	A*	`conf`	The Superposition of Diffusion Models Using the Itô Density Estimator. ICLR Marta Skreta, Lazar Atanackovic, Joey Bose, Alexander Tong, Kirill Neklyudov
2024	A*	`conf`	A Computational Framework for Solving Wasserstein Lagrangian Flows. ICML Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani
2024	Misc	`conf`	Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CISS Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2024	J	`jnl`	Generating Multi-Modal and Multi-Attribute Single-Cell Counts with CFGen. CoRR Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J. Theis
2024	J	`jnl`	ImageFlowNet: Forecasting Multiscale Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images. CoRR Chen Liu, Ke Xu, Liangbo L. Shen, Guillaume Huguet, Zilong Wang, Alexander Tong, Danilo Bzdok, Jay Stewart, Jay C. Wang, Luciano V. Del Priore, Smita Krishnaswamy
2024	J	`jnl`	Improving and generalizing flow-based generative models with minibatch optimal transport. Trans. Mach. Learn. Res. Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio
2024	A*	`conf`	Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. ICML 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
2024	J	`jnl`	Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR 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
2024	J	`jnl`	Learnable Filters for Geometric Scattering Modules. IEEE Trans. Signal Process. Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson D. Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf
2024	J	`jnl`	Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold. CoRR Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J. Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov
2024	A*	`conf`	Metric Flow Matching for Smooth Interpolations on the Data Manifold. NeurIPS Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Avishek Joey Bose, Francesco Di Giovanni
2024	J	`jnl`	Metric Flow Matching for Smooth Interpolations on the Data Manifold. CoRR Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alexander Tong, Michael M. Bronstein, Avishek Joey Bose, Francesco Di Giovanni
2024	A*	`conf`	SE(3)-Stochastic Flow Matching for Protein Backbone Generation. ICLR Avishek 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
2024	J	`jnl`	Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. CoRR Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose
2024	A*	`conf`	Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation. NeurIPS Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose
2024	A	`conf`	Simulation-Free Schrödinger Bridges via Score and Flow Matching. AISTATS Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
2024	J	`jnl`	Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. CoRR Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Zachary Quinn, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Yoshua Bengio, Pranam Chatterjee, Alexander Tong, Avishek Joey Bose
2024	J	`jnl`	The Superposition of Diffusion Models Using the Itô Density Estimator. CoRR Marta Skreta, Lazar Atanackovic, Avishek Joey Bose, Alexander Tong, Kirill Neklyudov
2024	J	`jnl`	Trajectory Flow Matching with Applications to Clinical Time Series Modeling. CoRR Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis L. Shung, Alexander Tong
2024	A*	`conf`	Trajectory Flow Matching with Applications to Clinical Time Series Modelling. NeurIPS Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis L. Shung, Alexander Tong
2023	J	`jnl`	A Computational Framework for Solving Wasserstein Lagrangian Flows. CoRR Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani
2023	A*	`conf`	A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. NeurIPS Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. CoRR Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CoRR Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems. CoRR Bailey Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu
2023	J	`jnl`	Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. CoRR Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio
2023	J	`jnl`	DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks. CoRR Lazar Atanackovic, Alexander Tong, Jason S. Hartford, Leo J. Lee, Bo Wang, Yoshua Bengio
2023	A*	`conf`	DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets. NeurIPS Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J. Lee, Yoshua Bengio, Jason S. Hartford
2023	—	`conf`	Geodesic Sinkhorn For Fast and Accurate Optimal Transport on Manifolds. MLSP Guillaume Huguet, Alexander Tong, María Ramos Zapatero, Christopher J. Tape, Guy Wolf, Smita Krishnaswamy
2023	J	`jnl`	Graph Fourier MMD for Signals on Graphs. CoRR Samuel Leone, Aarthi Venkat, Guillaume Huguet, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2023	J	`jnl`	Neural FIM for learning Fisher Information Metrics from point cloud data. CoRR Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	A*	`conf`	Neural FIM for learning Fisher information metrics from point cloud data. ICML Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	SE(3)-Stochastic Flow Matching for Protein Backbone Generation. CoRR Avishek Joey Bose, Tara Akhound-Sadegh, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong
2023	J	`jnl`	Simulation-free Schrödinger bridges via score and flow matching. CoRR Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
2023	J	`jnl`	Time-Inhomogeneous Diffusion Geometry and Topology. SIAM J. Math. Data Sci. Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
2023	J	`jnl`	Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms. SIAM J. Math. Data Sci. Michael Perlmutter, Alexander Tong, Feng Gao, Guy Wolf, Matthew J. Hirn
2022	Misc	`conf`	Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance. ICASSP Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators. J. Signal Process. Syst. Alexander Tong, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Geodesic Sinkhorn: optimal transport for high-dimensional datasets. CoRR Guillaume Huguet, Alexander Tong, María Ramos Zapatero, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Learnable Filters for Geometric Scattering Modules. CoRR Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson D. Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf
2022	A*	`conf`	Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. NeurIPS Guillaume Huguet, Daniel Sumner Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. CoRR Guillaume Huguet, Daniel Sumner Magruder, Oluwadamilola Fasina, Alexander Tong, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Time-inhomogeneous diffusion geometry and topology. CoRR Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
2021	—	`conf`	A sandbox for prediction and integration of DNA, RNA, and proteins in single cells. NeurIPS Datasets and Benchmarks Malte Lücken, Daniel Burkhardt, Robrecht Cannoodt, Christopher Lance, Aditi Agrawal, Hananeh Aliee, Ann Chen, Louise Deconinck, Angela Detweiler, Alejandro Granados, Shelly Huynh, Laura Isacco, Yang Kim, Dominik Klein, Bony de Kumar, Sunil Kuppasani, Heiko Lickert, Aaron McGeever, Joaquin Melgarejo, Honey Mekonen, Maurizio Morri, Michaela Müller, Norma Neff, Sheryl Paul, Bastian Rieck, Kaylie Schneider, Scott Steelman, Michael Sterr, Daniel Treacy, Alexander Tong, Alexandra-Chloé Villani, Guilin Wang, Jia Yan, Ce Zhang, Angela Pisco, Smita Krishnaswamy, Fabian J. Theis, Jonathan M. Bloom
2021	—	`conf`	Data-Driven Learning of Geometric Scattering Modules for GNNs. MLSP Alexander Tong, Frederick Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf
2021	A*	`conf`	Diffusion Earth Mover's Distance and Distribution Embeddings. ICML Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid MacDonald, Manik Kuchroo, Ronald R. Coifman, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	Diffusion Earth Mover's Distance and Distribution Embeddings. CoRR Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid MacDonald, Manik Kuchroo, Ronald R. Coifman, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. CoRR Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2021	—	`conf`	MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. IEEE BigData Michal Gerasimiuk, Dennis L. Shung, Alexander Tong, Adrian J. Stanley, Michael Schultz, Jeffrey Ngu, Loren Laine, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. CoRR Michal Gerasimiuk, Dennis L. Shung, Alexander Tong, Adrian J. Stanley, Michael Schultz, Jeffrey Ngu, Loren Laine, Guy Wolf, Smita Krishnaswamy
2021	—	`conf`	Multimodal Data Visualization and Denoising with Integrated Diffusion. MLSP Manik Kuchroo, Abhinav Godavarthi, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	POT: Python Optimal Transport. J. Mach. Learn. Res. 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
2020	J	`jnl`	Data-Driven Learning of Geometric Scattering Networks. CoRR Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf
2020	—	`conf`	Fixing Bias in Reconstruction-Based Anomaly Detection with Lipschitz Discriminators. MLSP Alexander Tong, Guy Wolf, Smita Krishnaswamy
2020	B	`conf`	Interpretable Neuron Structuring with Graph Spectral Regularization. IDA Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy
2020	A*	`conf`	TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. ICML Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
2020	J	`jnl`	TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. CoRR Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
2020	—	`conf`	Uncovering the Folding Landscape of RNA Secondary Structure Using Deep Graph Embeddings. IEEE BigData Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2020	J	`jnl`	Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. CoRR Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2019	J	`jnl`	A Lipschitz-constrained anomaly discriminator framework. CoRR Alexander Tong, Guy Wolf, Smita Krishnaswamy
2019	—	`conf`	Finding Archetypal Spaces Using Neural Networks. IEEE BigData David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2019	J	`jnl`	Finding Archetypal Spaces for Data Using Neural Networks. CoRR David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2018	A	`conf`	Allocate-On-Use Space Complexity of Shared-Memory Algorithms. DISC James Aspnes, Bernhard Haeupler, Alexander Tong, Philipp Woelfel
2018	J	`jnl`	Graph Spectral Regularization for Neural Network Interpretability. CoRR Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Guy Wolf, Smita Krishnaswamy