works on

From the 1 of 5.5k papers with an AI index.

output
19932026
most citedQuantum ESPRESSO: a modular and open-source software project for quantum simulations of materials

29.3k citations

5,497 papers

cs.CV2026

Temporal Periodic Image Registration with Implicit Neural Representations

Mathias Lowes, Kristine Aavild Sørensen, Maxime Sermesant +1

Implicit Neural Representations (INRs) have recently gained popularity for their ability to model functions using simple and lightweight networks. These methods have also proven ef…

math.NA2026

Neural Network Preconditioning: A Case Study for the Solution of the Parametric Helmholtz Equation

Luc Giraud, Carola Kruse, Paul Mycek +2

This work presents a hybrid numerical approach for solving linear systems arising from the discretization of the two-dimensional parametric Helmholtz equation. A convolutional neur…

cs.CC2026

Execution-Time Opacity in (Controllable) Timed Automata is Hard

Sarah Dépernet, Engel Lefaucheux

Timing information leakage occurs whenever an attacker successfully deduces confidential internal information by observing some timed information such as the total duration of a ru…

cs.LO2026

Antichains for Concurrent Parameterized Games

Nathalie Bertrand, Patricia Bouyer, Gaëtan Staquet

Concurrent parameterized games involve a fixed yet arbitrary number of players. They are described by finite arenas in which the edges are labeled with languages that describe the…

cs.LG2026

In a Streaming World, Should You Stand Still? A Comprehensive Benchmark of Anomaly Detection in Streams

Magali Parrino, Antoine Ajenjo, Emmanuel Remy +3

Time series anomaly detection (TSAD) is increasingly deployed in streaming settings, where data arrive sequentially and may exhibit non-stationarity. As a result, several works fro…

stat.ML2026

Machine Unlearning for Gibbs Supervised Learning Algorithms

Yaiza Bermudez, Samir M. Perlaza, Iñaki Esnaola

In this paper, a method for achieving exact unlearning for Gibbs supervised learning algorithms is proposed using a variational formulation inspired by empirical risk minimization…