output
20022026
most citedObservation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

10.9k citations

Showing 2023 · cs.LGShow all

9 papers · 2 filters

cs.LG2023★ 34 cited

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems

Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi +7

Recent advances in computational modelling of atomic systems, spanning molecules, proteins, and materials, represent them as geometric graphs with atoms embedded as nodes in 3D Euc…

cs.LG2023

Stochastic Average Gradient : A Simple Empirical Investigation

Pascal Junior Tikeng Notsawo

Despite the recent growth of theoretical studies and empirical successes of neural networks, gradient backpropagation is still the most widely used algorithm for training such netw…

cs.LG2023★ 20 cited

Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer Learning

Mohammad-Javad Darvishi-Bayazi, Mohammad Sajjad Ghaemi, Timothee Lesort +3

Pathology diagnosis based on EEG signals and decoding brain activity holds immense importance in understanding neurological disorders. With the advancement of artificial intelligen…

cs.LG2023★ 1 cited

Worrisome Properties of Neural Network Controllers and Their Symbolic Representations

Jacek Cyranka, Kevin E M Church, Jean-Philippe Lessard

We raise concerns about controllers' robustness in simple reinforcement learning benchmark problems. We focus on neural network controllers and their low neuron and symbolic abstra…

cs.LG2023★ 2 cited

Inferring dynamic regulatory interaction graphs from time series data with perturbations

Dhananjay Bhaskar, Sumner Magruder, Edward De Brouwer +4

Complex systems are characterized by intricate interactions between entities that evolve dynamically over time. Accurate inference of these dynamic relationships is crucial for und…

cs.LG2023★ 23 cited

RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark

Federico Berto, Chuanbo Hua, Junyoung Park +30

Combinatorial optimization (CO) is fundamental to several real-world applications, from logistics and scheduling to hardware design and resource allocation. Deep reinforcement lear…