activity
20082026
most citedA model for non-singular black hole collapse and evaporation

129 citations · 420 across the 16 of their papers we have counts for

collaborators

16 papers

cs.LG2026

TPR-Attention for Combinatorial Generalization

Melisa Civelekoğlu, Isabeau Prémont-Schwarz

Systematic generalization remains a significant challenge in deep learning. In particular, combinatorial generalization - generalizing to new configurations of known factors of var…

cs.NE2024

SNAP: Stopping Catastrophic Forgetting in Hebbian Learning with Sigmoidal Neuronal Adaptive Plasticity

Tianyi Xu, Patrick Zheng, Shiyan Liu +2

Artificial Neural Networks (ANNs) suffer from catastrophic forgetting, where the learning of new tasks causes the catastrophic forgetting of old tasks. Existing Machine Learning (M…

cs.LG2022★ 1 cited

A Simple Guard for Learned Optimizers

Isabeau Prémont-Schwarz, Jaroslav Vítků, Jan Feyereisl

If the trend of learned components eventually outperforming their hand-crafted version continues, learned optimizers will eventually outperform hand-crafted optimizers like SGD or…

cs.AI2020

Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization

Quentin Cappart, Thierry Moisan, Louis-Martin Rousseau +2

Combinatorial optimization has found applications in numerous fields, from aerospace to transportation planning and economics. The goal is to find an optimal solution among a finit…

cs.NE2017★ 11 cited

Recurrent Ladder Networks

Isabeau Prémont-Schwarz, Alexander Ilin, Tele Hotloo Hao +3

We propose a recurrent extension of the Ladder networks whose structure is motivated by the inference required in hierarchical latent variable models. We demonstrate that the recur…

gr-qc2012★ 19 cited

Emission spectra of self-dual black holes

Sabine Hossenfelder, Leonardo Modesto, Isabeau Prémont-Schwarz

We calculate the particle spectra of evaporating self-dual black holes that are potential dark matter candidates. We first estimate the relevant mass and temperature range and find…