Variable-Length Generative Protein Design via Generalized Poisson Flow | Paper Citation Record

Observation 53bac1b2-63e6-496c-8797-e57192baeb0c · outbound

This paper cites Lu, Nicolo Fusi, Ava P.

Variable-Length Generative Protein Design via Generalized Poisson Flow Lu, Nicolo Fusi, Ava P

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Observation 54ee6b7c-0f6c-4fb0-ac29-469d6a3c8ebb · outbound

This paper cites Structured denoising diffusion models in discrete state-spaces.Advances in neural information processing systems, 34:17981–17993, 2021.

Variable-Length Generative Protein Design via Generalized Poisson Flow Structured denoising diffusion models in discrete state-spaces.Advances in neural information processing systems, 34:17981–17993, 2021

Reference 2

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Observation c16812bc-5b23-47c3-afb2-25e81cb7a5ea · outbound

This paper cites Accurate prediction of protein structures and interactions using a three-track neural network.Science, 373(6557):871–876, 2021.

Variable-Length Generative Protein Design via Generalized Poisson Flow Accurate prediction of protein structures and interactions using a three-track neural network.Science, 373(6557):871–876, 2021

Reference 3

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Observation 4c0ef153-1d83-4f3a-80a6-0328707a173c · outbound

This paper cites Amin, Ruben Weitzman, Debora Marks, and Andrew Gordon Wilson.

Variable-Length Generative Protein Design via Generalized Poisson Flow Amin, Ruben Weitzman, Debora Marks, and Andrew Gordon Wilson

Reference 4

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Observation 40f3d3bb-e4e6-4158-a594-a58d649f036c · outbound

This paper cites The protein data bank.Nucleic acids research, 28(1):235–242, 2000.

Variable-Length Generative Protein Design via Generalized Poisson Flow The protein data bank.Nucleic acids research, 28(1):235–242, 2000

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Observation 4bd0fa96-7044-4d0f-8d75-fadf8a07d3bc · outbound

This paper cites An extension of watanabe’s theorem of characterization of poisson processes over the positive real half line.Journal of Applied Probability, 12(2):396–399, 1975.

Variable-Length Generative Protein Design via Generalized Poisson Flow An extension of watanabe’s theorem of characterization of poisson processes over the positive real half line.Journal of Applied Probability, 12(2):396–399, 1975

Reference 6

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Observation df112d5b-7652-44f5-aa75-33a71283ea6f · outbound

This paper cites Point processes and queues.Springer, 1981.

Variable-Length Generative Protein Design via Generalized Poisson Flow Point processes and queues.Springer, 1981

Reference 7

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Observation 2d5dedd9-6955-4b29-be5c-784de28e73ba · outbound

This paper cites De novo design of all-atom biomolecular interactions with rfdiffusion3.bioRxiv, 2025.

Variable-Length Generative Protein Design via Generalized Poisson Flow De novo design of all-atom biomolecular interactions with rfdiffusion3.bioRxiv, 2025

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Observation 2caeafef-10f9-4c87-a0af-0660bac59ac2 · outbound

This paper cites Trans-dimensional generative modeling via jump diffusion models.

Variable-Length Generative Protein Design via Generalized Poisson Flow Trans-dimensional generative modeling via jump diffusion models

Reference 9

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Observation 1daac3ec-d93c-4d81-b695-60ad03a12fe6 · outbound

This paper cites Pyrosetta: a script-based interface for implementing molecular modeling algorithms using rosetta.Bioinformatics, 26(5):689–691, 2010.

Variable-Length Generative Protein Design via Generalized Poisson Flow Pyrosetta: a script-based interface for implementing molecular modeling algorithms using rosetta.Bioinformatics, 26(5):689–691, 2010

Reference 10

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Observation 30fa9af4-aafe-4687-8314-21beb1219e23 · outbound

This paper cites Flow matching on general geometries.

Variable-Length Generative Protein Design via Generalized Poisson Flow Flow matching on general geometries

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Observation 5ca59f1a-a144-42b4-9cc1-2444e7c72bad · outbound

This paper cites Categorical flow matching on statistical manifolds.Advances in Neural Information Processing Systems, 37:54787–54819, 2024.

Variable-Length Generative Protein Design via Generalized Poisson Flow Categorical flow matching on statistical manifolds.Advances in Neural Information Processing Systems, 37:54787–54819, 2024

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Observation d26bf328-f78c-4c8b-9af8-806fdf93fa55 · outbound

This paper cites $\alpha$-Flow: A Unified Framework for Continuous-State Discrete Flow Matching Models.

Variable-Length Generative Protein Design via Generalized Poisson Flow $\alpha$-Flow: A Unified Framework for Continuous-State Discrete Flow Matching Models

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Observation 85924ab6-9b67-4b9a-bfde-d5ff31c28cc5 · outbound

This paper cites Springer, 2003.

Variable-Length Generative Protein Design via Generalized Poisson Flow Springer, 2003

Reference 14

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Observation b5334aa0-ce47-45ea-a385-9a1605e14c32 · outbound

This paper cites Robust deep learning–based protein sequence design using proteinmpnn.Science, 378(6615):49–56, 2022.

Variable-Length Generative Protein Design via Generalized Poisson Flow Robust deep learning–based protein sequence design using proteinmpnn.Science, 378(6615):49–56, 2022

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Observation bf420c55-4510-4595-8d36-96325343937d · outbound

This paper cites Mixed continuous and categorical flow matching for 3d de novo molecule generation.ArXiv, pages arXiv–2404, 2024.

Variable-Length Generative Protein Design via Generalized Poisson Flow Mixed continuous and categorical flow matching for 3d de novo molecule generation.ArXiv, pages arXiv–2404, 2024

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Observation 26477083-6131-4d01-94f0-3f03d49d1528 · outbound

This paper cites Discrete flow matching.Advances in Neural Information Processing Systems, 37:133345–133385, 2024.

Variable-Length Generative Protein Design via Generalized Poisson Flow Discrete flow matching.Advances in Neural Information Processing Systems, 37:133345–133385, 2024

Reference 17

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Observation 7a502c08-d913-4fb8-912e-f7a90f60e1d3 · outbound

This paper cites Proteina: Scaling Flow-based Protein Structure Generative Models.

Variable-Length Generative Protein Design via Generalized Poisson Flow Proteina: Scaling Flow-based Protein Structure Generative Models

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Observation 16fac3e2-9c16-43c1-bb09-18e3e549e252 · outbound

This paper cites Approximate accelerated stochastic simulation of chemically reacting systems.The Journal of chemical physics, 115(4):1716–1733, 2001.

Variable-Length Generative Protein Design via Generalized Poisson Flow Approximate accelerated stochastic simulation of chemically reacting systems.The Journal of chemical physics, 115(4):1716–1733, 2001

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Observation 56aa05ff-3212-4862-82f5-0057a3572723 · outbound

This paper cites Edit flows: Flow matching with edit operations.arXiv preprint arXiv:2506.09018, 2025.

Variable-Length Generative Protein Design via Generalized Poisson Flow Edit flows: Flow matching with edit operations.arXiv preprint arXiv:2506.09018, 2025

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Observation be54601a-61d3-4788-ab14-0c94d85e1678 · outbound

This paper cites Sofroniew, Deniz Oktay, Zeming Lin, Robert Verkuil, Vincent Q.

Variable-Length Generative Protein Design via Generalized Poisson Flow Sofroniew, Deniz Oktay, Zeming Lin, Robert Verkuil, Vincent Q

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Observation deae6e3d-d8fe-44eb-a86b-0932c7bfd83a · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

Variable-Length Generative Protein Design via Generalized Poisson Flow Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

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Observation 792d62da-e0a9-4b7b-94eb-ffc4d7226c4f · outbound

This paper cites Generator Matching: Generative modeling with arbitrary Markov processes.

Variable-Length Generative Protein Design via Generalized Poisson Flow Generator Matching: Generative modeling with arbitrary Markov processes

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Observation 9b14fed6-f80c-4c85-8132-489dbfea1872 · outbound

This paper cites Argmax flows and multinomial diffusion: Learning categorical distributions.Advances in neural information processing systems, 34:12454–12465, 2021.

Variable-Length Generative Protein Design via Generalized Poisson Flow Argmax flows and multinomial diffusion: Learning categorical distributions.Advances in neural information processing systems, 34:12454–12465, 2021

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Observation 3b4d5385-59ea-4e5f-b81d-6b387f7eb285 · outbound

This paper cites Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021.

Variable-Length Generative Protein Design via Generalized Poisson Flow Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021

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Observation 02f17ae2-ddac-4806-aaa8-46e90f7f81a4 · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features.Biopolymers, 22(12):2577–2637,

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Observation b0a5c1b9-8f60-4b80-beae-f50b721df445 · outbound

This paper cites an unresolved cited work.

Variable-Length Generative Protein Design via Generalized Poisson Flow Unresolved cited work

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Observation 6f483bde-1578-4521-831f-8af8748f8d3a · outbound

This paper cites Kingma and Jimmy Ba.

Variable-Length Generative Protein Design via Generalized Poisson Flow Kingma and Jimmy Ba

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Observation cab9df82-be7a-4a58-863c-4ad9c156a2cc · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Variable-Length Generative Protein Design via Generalized Poisson Flow Adam: A Method for Stochastic Optimization

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Observation ac8a7ea7-8cbb-4aad-a655-0e70a307c00d · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow Biotite: a unifying open source computational biology framework in Python.BMC Bioinformatics, 19(1):346, 2018

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Observation 14a8ec3b-9f06-41f1-b693-40c19212223a · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow Full-Atom Peptide Design based on Multi-modal Flow Matching

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Variable-Length Generative Protein Design via Generalized Poisson Flow Analysis of explicit tau-leaping schemes for simulating chemically reacting systems

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Observation bac450ba-9740-487a-b9bc-a85d8cba6d8e · outbound

This paper cites Out of Many, One: Designing and Scaffolding Proteins at the Scale of the Structural Universe with Genie 2.

Variable-Length Generative Protein Design via Generalized Poisson Flow Out of Many, One: Designing and Scaffolding Proteins at the Scale of the Structural Universe with Genie 2

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Variable-Length Generative Protein Design via Generalized Poisson Flow Evolutionary-scale prediction of atomic- level protein structure with a language model.Science, 379(6637):1123–1130, 2023

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Observation 1c94ecf8-9d50-4675-9ede-5fd581c309d3 · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023.

Variable-Length Generative Protein Design via Generalized Poisson Flow Evolutionary-scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023

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Observation 9342474b-a7fd-4207-a4c8-adb944569f8c · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow Flow Matching for Generative Modeling

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Variable-Length Generative Protein Design via Generalized Poisson Flow Multistate and functional protein design using rosettafold sequence space diffusion.Nature biotechnology, 43(8):1288–1298, 2025

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Observation d61d1359-0cee-4ed0-b7de-9ace8a86a543 · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow Rosetta flex- pepdock web server—high resolution modeling of peptide–protein interactions.Nucleic acids research, 39(suppl_2):W249–W253, 2011

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Observation e34fd0c2-5671-421f-bbb5-c915c6460914 · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow lDDT: A local superposition-free score for comparing protein structures and models using distance difference tests.Bioinformatics, 29(21):2722–2728, 2013

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Variable-Length Generative Protein Design via Generalized Poisson Flow Scalable Diffusion Models with Transformers

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Observation 061fb3de-cb49-40ff-a019-cfba1204c403 · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow Rosetta flexpepdock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors.PloS one, 6(4):e18934, 2011

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Variable-Length Generative Protein Design via Generalized Poisson Flow Fast solvers for discrete diffusion models: Theory and applications of high-order algorithms.arXiv preprint arXiv:2502.00234, 2025

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Variable-Length Generative Protein Design via Generalized Poisson Flow Simple and effective masked diffusion language models.Advances in Neural Information Processing Systems, 37:130136–130184, 2024

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Variable-Length Generative Protein Design via Generalized Poisson Flow Generative modeling by estimating gradients of the data distribution.Advances in neural information processing systems, 32, 2019

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Observation 09630efa-0b5b-4214-82bc-99be3af41098 · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets.Nature biotechnology, 35(11):1026–1028, 2017

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Variable-Length Generative Protein Design via Generalized Poisson Flow Suzek, Hongzhan Huang, Peter McGarvey, Raja Mazumder, and Cathy H

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Variable-Length Generative Protein Design via Generalized Poisson Flow UniProt: the Universal Protein Knowledgebase in 2023.Nucleic Acids Research, 51(D1):D523–D531, January 2023

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Variable-Length Generative Protein Design via Generalized Poisson Flow Fast and accurate protein structure search with foldseek.Nature biotechnology, 42(2):243–246, 2024

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Variable-Length Generative Protein Design via Generalized Poisson Flow A Comprehensive Review of Protein Language Models

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Variable-Length Generative Protein Design via Generalized Poisson Flow Diffusion Language Models Are Versatile Protein Learners

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Variable-Length Generative Protein Design via Generalized Poisson Flow De novo design of protein structure and function with rfdiffusion.Nature, 620(7976):1089–1100, 2023

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Variable-Length Generative Protein Design via Generalized Poisson Flow Fast protein backbone generation with SE(3) flow matching

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Variable-Length Generative Protein Design via Generalized Poisson Flow SE(3) diffusion model with application to protein backbone generation

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Variable-Length Generative Protein Design via Generalized Poisson Flow Scoring function for automated assessment of protein structure template quality.Proteins: Structure, Function, and Bioinformatics, 57(4):702–710,

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Observation 763f0e86-9a4d-4cd2-af80-d20700e1f4cd · outbound

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Variable-Length Generative Protein Design via Generalized Poisson Flow Unresolved cited work

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Observation 175a2a2e-8e2d-4f0a-868d-039ad47762f8 · outbound

This paper cites ut(x)· ∇logf(x) + 1 2 σ2 t ∇ · ∇logf(x) + Z [logf(y)−logf(x)]Q(dy|x) −˜ut(x)· ∇f(x) f(x) − 1 2 σ2 t ∇ · ∇f(x) f(x) − Z f(y) f(x) −1 ˜Q(dy|x) # (55) =E x∼pt.

Variable-Length Generative Protein Design via Generalized Poisson Flow ut(x)· ∇logf(x) + 1 2 σ2 t ∇ · ∇logf(x) + Z [logf(y)−logf(x)]Q(dy|x) −˜ut(x)· ∇f(x) f(x) − 1 2 σ2 t ∇ · ∇f(x) f(x) − Z f(y) f(x) −1 ˜Q(dy|x) # (55) =E x∼pt

Reference 56

Resolution: unresolved; no resolver link, observed 2026-07-13T00:48:08.651522Z

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Unavailable: canonical work link unavailable.

Observation 09237833-d78b-4ac3-90e8-baee608812b5 · outbound

This paper cites an unresolved cited work.

Variable-Length Generative Protein Design via Generalized Poisson Flow Unresolved cited work

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-13T00:48:08.651522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8aa26a6d-2802-40ae-88ca-c15268ad9ddd · outbound

This paper cites Inserted token identities are drawn from Qins tk,i(·|Xtk).

Variable-Length Generative Protein Design via Generalized Poisson Flow Inserted token identities are drawn from Qins tk,i(·|Xtk)

Reference 58

Resolution: unresolved; no resolver link, observed 2026-07-13T00:48:08.651522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef957939-2de7-4bf2-8805-581db438e0bd · outbound

This paper cites XtX i=0 λi t − XtX i=0 X k∈Ωi λeff k,t logλ i t # ,(98) and the modified reconstruction loss is: Lloc rec =E Y1,Yt.

Variable-Length Generative Protein Design via Generalized Poisson Flow XtX i=0 λi t − XtX i=0 X k∈Ωi λeff k,t logλ i t # ,(98) and the modified reconstruction loss is: Lloc rec =E Y1,Yt

Reference 59

Resolution: unresolved; no resolver link, observed 2026-07-13T00:48:08.651522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

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Outbound references

Pith citing papers