From the 6 of 288 papers with an AI index.
88 citations
- Centre National de la Recherche ScientifiqueFR114 papers
- University College LondonGB113 papers
- University of GenevaCH111 papers
- Université Paris-SaclayFR105 papers
- Sorbonne UniversitéFR101 papers
- University of BonnDE101 papers
- Institució Catalana de Recerca i Estudis AvançatsES100 papers
- University of BolognaIT100 papers
- University of OsloNO100 papers
- Université Paris CitéFR99 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di BolognaIT96 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di GenovaIT96 papers
10 papers · 1 filter
Symbolic Recovery of Differential Equations: The Identifiability Problem
Philipp Scholl, Aras Bacho, Holger Boche +1
Symbolic recovery of differential equations is the ambitious attempt at automating the derivation of governing equations with the use of machine learning techniques. In contrast to…
Tailored minimal reservoir computing: on the bidirectional connection between nonlinearities in the reservoir and in data
Davide Prosperino, Haochun Ma, Christoph Räth
We study how the degree of nonlinearity in the input data affects the optimal design of reservoir computers, focusing on how closely the model's nonlinearity should align with that…
Causal methods for LLM development and evaluation
Dennis Frauen, Marie Brockschmidt, Konstantin Hess +10
Large language model (LLM) development is currently driven by large-scale empirical iteration over data mixtures, reward models, routing strategies, and evaluation pipelines. Here,…
bde: A Python Package for Bayesian Deep Ensembles via MILE
Vyron Arvanitis, Angelos Aslanidis, Emanuel Sommer +1
bde is a user-friendly Python package for Bayesian Deep Ensembles with a particular focus on tabular data. Built on an efficient JAX implementation of the sampling-based inference…
Robustness Certificates for Neural Networks Against Data Poisoning and Evasion Attacks
Sara Taheri, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar +1
The increasing use of machine learning in safety-critical domains amplifies the risk of adversarial threats, especially data poisoning attacks that corrupt training data to degrade…
Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization
Chris Kolb, Christian L. Müller, Bernd Bischl +1
We present a framework for smooth optimization of explicitly regularized objectives for (structured) sparsity. These non-smooth and possibly non-convex problems typically rely on s…