Andrew M. Watkins

Orcid: 0000-0003-1617-1720

Affiliations:
  • New York University, Department of Chemistry, New York City, NY, USA (PhD)


According to our database1, Andrew M. Watkins authored at least 20 papers between 2013 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Disentangling multispecific antibody function with graph neural networks.
CoRR, January, 2026

2025
Unified all-atom molecule generation with neural fields.
CoRR, November, 2025

Do we need equivariant models for molecule generation?
CoRR, July, 2025

Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins.
CoRR, July, 2025

Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024
LLMs are Highly-Constrained Biophysical Sequence Optimizers.
CoRR, 2024

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design.
CoRR, 2024

NEBULA: Neural Empirical Bayes Under Latent Representations for Efficient and Controllable Design of Molecular Libraries.
CoRR, 2024

Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms.
CoRR, 2024

2023
MoleCLUEs: Optimizing Molecular Conformers by Minimization of Differentiable Uncertainty.
CoRR, 2023

SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers.
CoRR, 2023

3D molecule generation by denoising voxel grids.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

OpenProteinSet: Training data for structural biology at scale.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Deep learning models for predicting RNA degradation via dual crowdsourcing.
Nat. Mac. Intell., December, 2022

PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design.
CoRR, 2022

Multi-segment preserving sampling for deep manifold sampler.
CoRR, 2022

2021
Predictive models of RNA degradation through dual crowdsourcing.
CoRR, 2021

2020
Better together: Elements of successful scientific software development in a distributed collaborative community.
PLoS Comput. Biol., 2020

2016
Accurate <i>de novo</i> design of hyperstable constrained peptides.
Nat., 2016

2013
HippDB: a database of readily targeted helical protein-protein interactions.
Bioinform., 2013


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