3 papers
cs.LG2026
E3J: An Efficient and Open-Source Backend for Euclidean Equivariant Operations on GPU and TPU
Olivier Peltre, Armand Picard, Adrien Pichard +6
We present e3j, a fast Euclid-equivariance backend for geometric deep learning applications with JAX bindings for GPU and TPU. Leveraging both optimized CUDA and Pallas kernels and…
cs.NI2025
Learning-Based vs Human-Derived Congestion Control: An In-Depth Experimental Study
Mihai Mazilu, Luca Giacomoni, George Parisis
Learning-based congestion control (CC), including Reinforcement-Learning, promises efficient CC in a fast-changing networking landscape, where evolving communication technologies,…
cs.NI2023
RayNet: A Simulation Platform for Developing Reinforcement Learning-Driven Network Protocols
Luca Giacomoni, Basil Benny, George Parisis
Reinforcement Learning (RL) has gained significant momentum in the development of network protocols. However, RL-based protocols are still in their infancy, and substantial researc…