3 citations · 4 across the 6 of their papers we have counts for
6 papers
Exact Law of Quantum Reversibility under Gaussian Pure Loss
Ammar Fayad
Classical reverse diffusion is generated by changing the drift at fixed noise. We show that the quantum version of this principle obeys an exact law with a sharp phase boundary. Fo…
Score Reversal Is Not Free for Quantum Diffusion Models
Ammar Fayad
Classical reverse diffusion is generated by changing the drift at fixed noise. We show that the quantum version of this principle obeys an exact law with a sharp phase boundary. Fo…
Unsupervised Learning Approach to Anomaly Detection in Gravitational Wave Data
Ammar Fayad
Gravitational waves (GW), predicted by Einstein's General Theory of Relativity, provide a powerful probe of astrophysical phenomena and fundamental physics. In this work, we propos…
Hierarchical Strategies for Cooperative Multi-Agent Reinforcement Learning
Majd Ibrahim, Ammar Fayad
Adequate strategizing of agents behaviors is essential to solving cooperative MARL problems. One intuitively beneficial yet uncommon method in this domain is predicting agents futu…
Influence-Based Reinforcement Learning for Intrinsically-Motivated Agents
Ammar Fayad, Majd Ibrahim
Discovering successful coordinated behaviors is a central challenge in Multi-Agent Reinforcement Learning (MARL) since it requires exploring a joint action space that grows exponen…
Behavior-Guided Actor-Critic: Improving Exploration via Learning Policy Behavior Representation for Deep Reinforcement Learning
Ammar Fayad, Majd Ibrahim
In this work, we propose Behavior-Guided Actor-Critic (BAC), an off-policy actor-critic deep RL algorithm. BAC mathematically formulates the behavior of the policy through autoenco…