Publications

(2024). Trajectory Flow Matching with Applications to Clinical Time Series Modeling. In NeurIPS (Spotlight).

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(2024). Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. In NeurIPS.

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(2024). Metric Flow Matching for Smooth Interpolations on the Data Manifold. In NeurIPS.

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(2024). Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. Preprint.

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(2024). Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. In ICML.

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(2024). A Computational Framework for Solving Wasserstein Lagrangian Flows. In ICML.

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(2024). Defining and Benchmarking Open Problems in Single-Cell Analysis. Preprint.

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(2024). SE(3)-Stochastic Flow Matching for Protein Backbone Generation. In ICLR (Spotlight).

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(2024). Simulation-Free Schrodinger Bridges via Score and Flow Matching. In AISTATS.
Also presented at Frontiers4LCD Workshop @ ICML 2023.

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(2024). Learnable Filters for Geometric Scattering Modules. In IEEE Transactions on Signal Processing.

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(2024). Generating Multi-Modal and Multi-Attribute Single-Cell Counts with CFGen. Preprint.

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(2023). Trellis tree-based analysis reveals stromal regulation of patient-derived organoid drug responses. Cell.

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(2023). Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms. In SIMODS.

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(2023). DynGFN: Bayesian Dynamic Causal Discovery Using Generative Flow Networks. In NeurIPS.
Also presented at Frontiers4LCD Workshop @ NeurIPS 2022.

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(2023). A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. In NeurIPS.

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(2023). Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems. arXiv.

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(2023). Neural FIM for Learning Fisher Information Metrics from Point Cloud Data. In ICML.

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(2023). Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds. In IEEE MLSP.

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(2023). Time-Inhomogeneous Diffusion Geometry and Topology. In SIMODS.

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(2023). Single-Cell Analysis Reveals Inflammatory Interactions Driving Macular Degeneration. Nature Communications.

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(2023). Learning Transcriptional and Regulatory Dynamics Driving Cancer Cell Plasticity Using Neural ODE-Based Optimal Transport. BioRxiv.

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(2023). Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport. In TMLR
Also presented at Frontiers4LCD Workshop @ ICML 2023.

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(2023). Graph Fourier MMD for signals on data graphs. In SAMPTA.

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(2022). Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. In NeurIPS.

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(2022). Immune Cells and Their Inflammatory Mediators Modify Beta Cells and Cause Checkpoint Inhibitor-Induced Diabetes. JCI Insight.

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(2022). Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. In ICASSP.

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(2022). Topological Analysis of Single-Cell Hierarchy Reveals Inflammatory Glial Landscape of Macular Degeneration. Investigative Ophthalmology & Visual Science.

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(2022). Multiscale PHATE identifies multimodal signatures of COVID-19. Nature Biotechnology.

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(2021). MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. In IEEE Big Data.

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(2021). A sandbox for prediction and integration of DNA, RNA, and protein data in single cells. In NeurIPS Datasets and Benchmarks.

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(2021). Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators. In Journal of Signal Processing Systems.

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(2021). Multimodal data visualization and denoising with integrated diffusion. In IEEE MLSP.

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(2021). Data-Driven Learning of Geometric Scattering Networks. In IEEE MLSP.
Also presented at ML4M Workshop @ NeurIPS 2020.

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(2021). Diffusion Earth Mover's Distance and Distribution Embeddings. In ICML.
Also presented at LMRL Workshop @ NeurIPS 2020.

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(2021). POT: Python Optimal Transport. In JMLR.

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(2021). Quantifying the effect of experimental perturbations in single-cell RNA-sequencing data using graph signal processing. In Nature Biotechnology.

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(2020). Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. In IEEE Big Data.
Also at GRLB Workshop @ ICML 2020.

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(2020). TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. In ICML.
Also at LMRL Workshop @ NeurIPS 2019.

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(2020). Interpretable Neuron Structuring with Graph Spectral Regularization. In IDA
Also presented at RLGM Workshop @ ICLR 2019.

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(2019). Finding Archetypal Spaces Using Neural Networks. In IEEE Big Data.

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(2018). Allocate-On-Use Space Complexity of Shared-Memory Algorithms. In DISC.

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