E-LIB Suche - Ergebnisse für: Schwarzer, Max

1

Discovering the Electron Beam Induced Transition Rates for ..:

Roccapriore, Kevin M ; Schwarzer, Max ; Greaves, Joshua...
Microscopy and Microanalysis. 29 (2023) Supplement_1 - p. 1932-1933 , 2023

Link: https://doi.org/10.1093/..

2

Blockchain Technology in Supply Chain Management – A Discus..:

, In: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Science and Technologies for Smart Cities,

Gürpinar, Tan ; Große, Nick ; Schwarzer, Max... - p. 482-503 , 2022

Link: https://doi.org/10.1007/..

3

To join or not to join?–A framework for the evaluation of e..:

Schwarzer, Max ; Gürpinar, Tan ; Henke, Michael
Frontiers in Blockchain. 5 (2022) - p. , 2022

Link: https://doi.org/10.3389/..

4

Learning to fail: Predicting fracture evolution in brittle ..:

Schwarzer, Max ; Rogan, Bryce ; Ruan, Yadong...
Computational Materials Science. 162 (2019) - p. 322-332 , 2019

Link: https://doi.org/10.1016/..

5

Large Language Models as Generalizable Policies for Embodie..:

Szot, Andrew ; Schwarzer, Max ; Agrawal, Harsh...
http://arxiv.org/abs/2310.17722. , 2023

Link: http://arxiv.org/abs/231..

6

Learning and Controlling Silicon Dopant Transitions in Grap..:

Schwarzer, Max ; Farebrother, Jesse ; Greaves, Joshua...
http://arxiv.org/abs/2311.17894. , 2023

Link: http://arxiv.org/abs/231..

7

Bigger, Better, Faster: Human-level Atari with human-level ..:

Schwarzer, Max ; Obando-Ceron, Johan ; Courville, Aaron...
http://arxiv.org/abs/2305.19452. , 2023

Link: http://arxiv.org/abs/230..

8

Simplicial Embeddings in Self-Supervised Learning and Downs..:

Lavoie, Samuel ; Tsirigotis, Christos ; Schwarzer, Max...
http://arxiv.org/abs/2204.00616. , 2022

Link: http://arxiv.org/abs/220..

9

Reincarnating Reinforcement Learning: Reusing Prior Computa..:

Agarwal, Rishabh ; Schwarzer, Max ; Castro, Pablo Samuel..
http://arxiv.org/abs/2206.01626. , 2022

Link: http://arxiv.org/abs/220..

10

To join or not to join?–A framework for the evaluation of e..:

Schwarzer, Max ; Gürpinar, Tan ; Henke, Michael
http://hdl.handle.net/2003/41080. , 2022

Link: http://hdl.handle.net/20..

11

The Primacy Bias in Deep Reinforcement Learning:

Nikishin, Evgenii ; Schwarzer, Max ; D'Oro, Pierluca..
http://arxiv.org/abs/2205.07802. , 2022

Link: http://arxiv.org/abs/220..

12

Iterated learning for emergent systematicity in VQA:

Vani, Ankit ; Schwarzer, Max ; Lu, Yuchen..
http://arxiv.org/abs/2105.01119. , 2021

Link: http://arxiv.org/abs/210..

13

Pretraining Representations for Data-Efficient Reinforcemen..:

Schwarzer, Max ; Rajkumar, Nitarshan ; Noukhovitch, Michael...
http://arxiv.org/abs/2106.04799. , 2021

Link: http://arxiv.org/abs/210..

14

Deep Reinforcement Learning at the Edge of the Statistical ..:

Agarwal, Rishabh ; Schwarzer, Max ; Castro, Pablo Samuel..
http://arxiv.org/abs/2108.13264. , 2021

Link: http://arxiv.org/abs/210..

15

Data-Efficient Reinforcement Learning with Self-Predictive ..:

Schwarzer, Max ; Anand, Ankesh ; Goel, Rishab...
http://arxiv.org/abs/2007.05929. , 2020

Link: http://arxiv.org/abs/200..