182 citations · 312 across the 3 of their papers we have counts for
3 papers
Distral: Robust Multitask Reinforcement Learning
Yee Whye Teh, Victor Bapst, Wojciech Marian Czarnecki +5
Most deep reinforcement learning algorithms are data inefficient in complex and rich environments, limiting their applicability to many scenarios. One direction for improving data…
The effect of quantum fluctuations on the coloring of random graphs
Victor Bapst, Guilhem Semerjian, Francesco Zamponi
We present a study of the coloring problem (antiferromagnetic Potts model) of random regular graphs, submitted to quantum fluctuations induced by a transverse field, using the quan…
The Quantum Adiabatic Algorithm applied to random optimization problems: the quantum spin glass perspective
Victor Bapst, Laura Foini, Florent Krzakala +2
Among various algorithms designed to exploit the specific properties of quantum computers with respect to classical ones, the quantum adiabatic algorithm is a versatile proposition…