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Sam Dillavou
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Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
11752022
Demonstration of decentralized physics-driven learning
S Dillavou, M Stern, AJ Liu, DJ Durian
Physical Review Applied 18 (1), 014040, 2022
722022
Nonmonotonic aging and memory in a frictional interface
S Dillavou, SM Rubinstein
Physical review letters 120 (22), 224101, 2018
672018
Anatomic variation of depth‐dependent mechanical properties in neonatal bovine articular cartilage
JL Silverberg, S Dillavou, L Bonassar, I Cohen
Journal of Orthopaedic Research 31 (5), 686-691, 2013
492013
Desynchronous learning in a physics-driven learning network
JF Wycoff, S Dillavou, M Stern, AJ Liu, DJ Durian
The Journal of Chemical Physics 156 (14), 2022
302022
Physical learning beyond the quasistatic limit
M Stern, S Dillavou, MZ Miskin, DJ Durian, AJ Liu
Physical Review Research 4 (2), L022037, 2022
272022
Shear controls frictional aging by erasing memory
S Dillavou, SM Rubinstein
Physical Review Letters 124 (8), 085502, 2020
172020
Influences of microcontact shape on the state of a frictional interface
T Pilvelait, S Dillavou, SM Rubinstein
Physical Review Research 2 (1), 012056, 2020
132020
Machine learning without a processor: Emergent learning in a nonlinear analog network
S Dillavou, BD Beyer, M Stern, AJ Liu, MZ Miskin, DJ Durian
Proceedings of the National Academy of Sciences 121 (28), e2319718121, 2024
11*2024
The virtual frame technique: ultrafast imaging with any camera
S Dillavou, SM Rubinstein, JM Kolinski
Optics Express 27 (6), 8112-8120, 2019
112019
Aqueous foams in microgravity, measuring bubble sizes
M Pasquet, N Galvani, O Pitois, S Cohen-Addad, R Höhler, AT Chieco, ...
Comptes Rendus. Mécanique 351 (S2), 139-161, 2023
102023
Training self-learning circuits for power-efficient solutions
M Stern, S Dillavou, D Jayaraman, DJ Durian, AJ Liu
APL Machine Learning 2 (1), 2024
9*2024
Circuits that train themselves: decentralized, physics-driven learning
S Dillavou, B Beyer, M Stern, MZ Miskin, AJ Liu, DJ Durian
AI and Optical Data Sciences IV 12438, 115-117, 2023
82023
Spatters and spills: Spreading dynamics for partially wetting droplets
SCL Durian, S Dillavou, K Markin, A Portales, BOT Maldonado, W Irvine, ...
Physics of Fluids 34 (1), 2022
62022
Seismological stress drops for confined ruptures are invariant to normal stress
W Steinhardt, S Dillavou, M Agajanian, SM Rubinstein, EE Brodsky
Geophysical Research Letters 50 (9), e2022GL101366, 2023
52023
Cornerstones are the key stones: Using interpretable machine learning to probe the clogging process in 2D granular hoppers
JM Hanlan, S Dillavou, AJ Liu, DJ Durian
arXiv preprint arXiv:2407.05491, 2024
32024
Beyond quality and quantity: Spatial distribution of contact encodes frictional strength
S Dillavou, Y Bar-Sinai, MP Brenner, SM Rubinstein
Physical Review E 106 (3), L033001, 2022
32022
Air mediates the impact of a compliant hemisphere on a rigid smooth surface
S Zheng, S Dillavou, JM Kolinski
Soft Matter 17 (14), 3813-3819, 2021
32021
Equation of motion for taut-line buzzers
AJ Gerra, CC Jones, S Dillavou, JM Hanlan, J Radzio, PE Arratia, ...
Physical Review Applied 22 (1), 014011, 2024
22024
Nonlinear Classification Without a Processor
S Dillavou, B Beyer, M Stern, M Miskin, A Liu, D Durian
Machine Learning with New Compute Paradigms, 2023
22023
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