1.4k citations
- Centre National de la Recherche ScientifiqueFR302 papers
- Laboratoire de Physique Subatomique et des Technologies AssociéesFR235 papers
- Laboratoire des Sciences du Numérique de NantesFR125 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR97 papers
- IMT AtlantiqueFR81 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR80 papers
- Universidade de São PauloBR79 papers
- National Institute for Subatomic PhysicsNL78 papers
- The Ohio State UniversityUS74 papers
- Brookhaven National LaboratoryUS69 papers
- Institute for High Energy PhysicsES68 papers
- Joint Institute for Nuclear ResearchRU67 papers
43 papers · 1 filter
On the Conical Novikov Homology
A. Pajitnov
Let be a Morse form on a manifold . Let be a regular covering with structure group , such that . Let be the corresponding p…
Design of Optimal Multiplierless FIR Filters
Martin Kumm, Anastasia Volkova, Silviu-Ioan Filip
This work presents two novel optimization methods based on integer linear programming (ILP) that minimize the number of adders used to implement a direct/transposed finite impulse…
A simple and efficient dichotomic search algorithm for multi-objective mixed integer linear programs
Anthony Przybylski, Kathrin Klamroth, Renaud Lacour
We present a simple and at the same time fficient algorithm to compute all nondominated extreme points in the outcome set of multi-objective mixed integer linear programmes in any…
A New Ensemble Adversarial Attack Powered by Long-term Gradient Memories
Zhaohui Che, Ali Borji, Guangtao Zhai +3
Deep neural networks are vulnerable to adversarial attacks.
Combined sensitivity to the neutrino mass ordering with JUNO, the IceCube Upgrade, and PINGU
Gen2 Collaboration, M. G. Aartsen, M. Ackermann +440
The ordering of the neutrino mass eigenstates is one of the fundamental open questions in neutrino physics. While current-generation neutrino oscillation experiments are able to pr…
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration
Meelis Kull, Miquel Perello-Nieto, Markus Kängsepp +3
Class probabilities predicted by most multiclass classifiers are uncalibrated, often tending towards over-confidence. With neural networks, calibration can be improved by temperatu…