Ryan P. Adams

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Dive into the research topics where Ryan P. Adams is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

2 Finished

RI: Small: Accelerating Machine Learning via Randomized Automatic Differentiation
Adams, R. P. (PI)
NSF - National Science Foundation
10/1/20 → 9/30/24
Project: Research project
RI: Small: Parallel Markov Chain Monte Carlo Methods for Scalable Bayesian Inference
Adams, R. P. (PI)
NSF - National Science Foundation
9/1/17 → 8/31/20
Project: Research project

51 Conference contribution
27 Conference article
20 Article
11 Paper
More

A rapid and automated computational approach to the design of multistable soft actuators
Mirramezani, M., Oktay, D. & Adams, R. P., May 2024, In: Computer Physics Communications. 298, 109090.
Research output: Contribution to journal › Article › peer-review
2 Scopus citations
Automated discovery of reprogrammable nonlinear dynamic metamaterials
Bordiga, G., Medina, E., Jafarzadeh, S., Bösch, C., Adams, R. P., Tournat, V. & Bertoldi, K., Nov 2024, In: Nature Materials. 23, 11, p. 1486-1494 9 p.
Research output: Contribution to journal › Article › peer-review
10 Scopus citations
FIBER MONTE CARLO
Richardson, N., Oktay, D., Ovadia, Y., Bowden, J. C. & Adams, R. P., 2024.
Research output: Contribution to conference › Paper › peer-review
Generative Marginalization Models
Liu, S., Ramadge, P. J. & Adams, R. P., 2024, In: Proceedings of Machine Learning Research. 235, p. 31773-31807 35 p.
Research output: Contribution to journal › Conference article › peer-review
Probabilistic prediction of material stability: integrating convex hulls into active learning
Novick, A., Cai, D., Nguyen, Q., Garnett, R., Adams, R. & Toberer, E., Aug 5 2024, In: Materials Horizons. 11, 21, p. 5381-5393 13 p.
Research output: Contribution to journal › Article › peer-review

Open Access
3 Scopus citations

Ryan P. Adams

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Collaborations and top research areas from the last five years

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RI: Small: Accelerating Machine Learning via Randomized Automatic Differentiation

RI: Small: Parallel Markov Chain Monte Carlo Methods for Scalable Bayesian Inference

A rapid and automated computational approach to the design of multistable soft actuators

Automated discovery of reprogrammable nonlinear dynamic metamaterials

FIBER MONTE CARLO

Generative Marginalization Models

Probabilistic prediction of material stability: integrating convex hulls into active learning

Ryan P. Adams

Fingerprint

Collaborations and top research areas from the last five years

Projects

RI: Small: Accelerating Machine Learning via Randomized Automatic Differentiation

RI: Small: Parallel Markov Chain Monte Carlo Methods for Scalable Bayesian Inference

Research output

A rapid and automated computational approach to the design of multistable soft actuators

Automated discovery of reprogrammable nonlinear dynamic metamaterials

FIBER MONTE CARLO

Generative Marginalization Models

Probabilistic prediction of material stability: integrating convex hulls into active learning