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Victor Bapst
Victor Bapst
Bestätigte E-Mail-Adresse bei math.uni-frankfurt.de
Titel
Zitiert von
Zitiert von
Jahr
Relational inductive biases, deep learning, and graph networks
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
23282018
Sample efficient actor-critic with experience replay
Z Wang, V Bapst, N Heess, V Mnih, R Munos, K Kavukcuoglu, ...
arXiv preprint arXiv:1611.01224, 2016
7802016
Distral: Robust multitask reinforcement learning
Y Teh, V Bapst, WM Czarnecki, J Quan, J Kirkpatrick, R Hadsell, N Heess, ...
Advances in neural information processing systems 30, 2017
4542017
Relational deep reinforcement learning
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
arXiv preprint arXiv:1806.01830, 2018
2182018
Hyperbolic attention networks
C Gulcehre, M Denil, M Malinowski, A Razavi, R Pascanu, KM Hermann, ...
arXiv preprint arXiv:1805.09786, 2018
1822018
Unveiling the predictive power of static structure in glassy systems
V Bapst, T Keck, A Grabska-Barwińska, C Donner, ED Cubuk, ...
Nature Physics 16 (4), 448-454, 2020
1802020
The quantum adiabatic algorithm applied to random optimization problems: The quantum spin glass perspective
V Bapst, L Foini, F Krzakala, G Semerjian, F Zamponi
Physics Reports 523 (3), 127-205, 2013
1552013
Deep reinforcement learning with relational inductive biases
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
International conference on learning representations, 2018
1442018
Hamiltonian graph networks with ode integrators
A Sanchez-Gonzalez, V Bapst, K Cranmer, P Battaglia
arXiv preprint arXiv:1909.12790, 2019
1052019
Relational inductive bias for physical construction in humans and machines
JB Hamrick, KR Allen, V Bapst, T Zhu, KR McKee, JB Tenenbaum, ...
arXiv preprint arXiv:1806.01203, 2018
952018
Anomalous Softening of Crystals
X Rojas, A Haziot, V Bapst, S Balibar, HJ Maris
Physical Review Letters 105 (14), 145302, 2010
902010
Relational inductive biases, deep learning, and graph networks. arXiv 2018
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
852018
Structured agents for physical construction
V Bapst, A Sanchez-Gonzalez, C Doersch, K Stachenfeld, P Kohli, ...
International conference on machine learning, 464-474, 2019
662019
On quantum mean-field models and their quantum annealing
V Bapst, G Semerjian
Journal of Statistical Mechanics: Theory and Experiment 2012 (06), P06007, 2012
632012
Generating interpretable images with controllable structure
S Reed, A van den Oord, N Kalchbrenner, V Bapst, M Botvinick, ...
562016
The condensation phase transition in random graph coloring
V Bapst, A Coja-Oghlan, S Hetterich, F Raßmann, D Vilenchik
Communications in Mathematical Physics 341 (2), 543-606, 2016
562016
Combining q-learning and search with amortized value estimates
JB Hamrick, V Bapst, A Sanchez-Gonzalez, T Pfaff, T Weber, L Buesing, ...
arXiv preprint arXiv:1912.02807, 2019
402019
Harnessing the Bethe free energy
V Bapst, A Coja‐Oghlan
Random structures & algorithms 49 (4), 694-741, 2016
332016
Relational inductive biases, deep learning, and graph networks. arXiv e-prints
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
232018
The large connectivity limit of the Anderson model on tree graphs
V Bapst
Journal of Mathematical Physics 55 (9), 092101, 2014
232014
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