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SE(3)-Stochastic Flow Matching for Protein Backbone Generation
We present FoldFlow a novel flow matching model for protein design. We present theory and practical tricks for flow models over SE(3)^N. Empirically, we validate these models on protein backbone generation of up to 300 amino acids leading to high-quality designable, diverse, and novel samples.
Avishek Joey Bose, Tara Akhound-Sadegh, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael Bronstein, Alex Tong
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SE(3)-Stochastic Flow Matching for Protein Backbone Generation
Simulation-Free Schrodinger Bridges via Score and Flow Matching
We present simulation-free score and flow matching ([SF]2M), a simulation-free objective for inferring stochastic dynamics given …
Alex Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
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Learnable Filters for Geometric Scattering Modules
Alex Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid Macdonald, Jackson Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf
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Trellis tree-based analysis reveals stromal regulation of patient-derived organoid drug responses
Trellis is a tree-based earth mover’s distance method for understanding estimating treatment effects from single cell data. In this work we apply it to colorectal cancer PDOS and investigate the chemoprotection induced by cancer-associated fibroblasts.
María Ramos Zapatero, Alex Tong, Jahangir Sufi, Petra Vlckova, Ferran Cardoso Rodriguez, Callum Nattress, Xiao Qin, Daniel Hochhauser, Smita Krishnaswamy, Christopher J. Tape
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Trellis tree-based analysis reveals stromal regulation of patient-derived organoid drug responses
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction
Guillaume Huguet, Alex Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy
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DynGFN: Bayesian Dynamic Causal Discovery Using Generative Flow Networks
One of the grand challenges of cell biology is inferring the gene regulatory network (GRN) which describes interactions between genes …
Lazar Atanackovic, Alex Tong, Jason Hartford, Leo J. Lee, Bo Wang, Yoshua Bengio
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DynGFN: Bayesian Dynamic Causal Discovery Using Generative Flow Networks
Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms
The scattering transform is a multilayered wavelet-based deep learning architecture that acts as a model of convolutional neural …
Michael Perlmutter, Alex Tong, Feng Gao, Guy Wolf, Matthew Hirn
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Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds
Efficient computation of optimal transport distance between distributions is of growing importance in data science. Sinkhorn-based …
Guillaume Huguet, Alex Tong, María Ramos Zapatero, Christpher J. Tape, Guy Wolf, Smita Krishnaswamy
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Neural FIM for Learning Fisher Information Metrics from Point Cloud Data
Oluwadamilola Fasina, Guillaume Huguet, Alex Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
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Time-Inhomogeneous Diffusion Geometry and Topology
Diffusion condensation is a dynamic process that yields a sequence of multiscale data representations that aim to encode meaningful …
Guillaume Huguet, Alex Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew Hirn, Guy Wolf, Smita Krishnaswamy
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