:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	De Geeter, Florent, Lambrechts, Gaspard, Ernst, Damien, Drion, Guillaume
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2601.09495
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Spike-based computation using classical recurrent neural networks
by: De Geeter, Florent, et al.
Published: (2023)

Improving the Performance and Learning Stability of Parallelizable RNNs Designed for Ultra-Low Power Applications
by: Brandoit, Julien, et al.
Published: (2026)

On the Importance of Multistability for Horizon Generalization in Reinforcement Learning
by: Bakija, Asad, et al.
Published: (2026)

Maximum-Entropy Exploration with Future State-Action Visitation Measures
by: Bolland, Adrien, et al.
Published: (2026)

Behind the Myth of Exploration in Policy Gradients
by: Bolland, Adrien, et al.
Published: (2024)

Informed POMDP: Leveraging Additional Information in Model-Based RL
by: Lambrechts, Gaspard, et al.
Published: (2023)

A Theoretical Justification for Asymmetric Actor-Critic Algorithms
by: Lambrechts, Gaspard, et al.
Published: (2025)

Off-Policy Maximum Entropy RL with Future State and Action Visitation Measures
by: Bolland, Adrien, et al.
Published: (2024)

Energy-Efficient Implementation of Spiking Recurrent Cells on FPGA
by: Harmeling, Pascal, et al.
Published: (2026)

Informed Asymmetric Actor-Critic: Leveraging Privileged Signals Beyond Full-State Access
by: Ebi, Daniel, et al.
Published: (2025)

Parallelizing Autoregressive Generation with Variational State Space Models
by: Lambrechts, Gaspard, et al.
Published: (2024)

Fast reconstruction of degenerate populations of conductance-based neuron models from spike times
by: Brandoit, Julien, et al.
Published: (2025)

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations
by: Fyon, Arthur, et al.
Published: (2026)

Reinforcement Learning to improve delta robot throws for sorting scrap metal
by: Louette, Arthur, et al.
Published: (2024)

MINIMALIST: switched-capacitor circuits for efficient in-memory computation of gated recurrent units
by: Billaudelle, Sebastian, et al.
Published: (2025)

Context-dependent manifold learning: A neuromodulated constrained autoencoder approach
by: Adriaens, Jérôme, et al.
Published: (2026)

Real-World Reinforcement Learning of Active Perception Behaviors
by: Hu, Edward S., et al.
Published: (2025)

Why Are Linear RNNs More Parallelizable?
by: Merrill, William, et al.
Published: (2026)

ParaRNN: An Interpretable and Parallelizable Recurrent Neural Network for Time-Dependent Data
by: Cai, Yuxi, et al.
Published: (2026)

Why Depth Matters in Parallelizable Sequence Models: A Lie Algebraic View
by: Heo, Gyuryang, et al.
Published: (2026)

Gym-TORAX: Open-source software for integrating reinforcement learning with plasma control simulators in tokamak research
by: Mouchamps, Antoine, et al.
Published: (2025)

Cost Estimation in Unit Commitment Problems Using Simulation-Based Inference
by: Pirlet, Matthias, et al.
Published: (2024)

Bregman Conditional Random Fields: Sequence Labeling with Parallelizable Inference Algorithms
by: Corro, Caio, et al.
Published: (2025)

Unlocking the Power of Boltzmann Machines by Parallelizable Sampler and Efficient Temperature Estimation
by: Kubo, Kentaro, et al.
Published: (2025)

Fading memory as inductive bias in residual recurrent networks
by: Dubinin, Igor, et al.
Published: (2023)

KQ-SVD: Compressing the KV Cache with Provable Guarantees on Attention Fidelity
by: Lesens, Damien, et al.
Published: (2025)

Practical and Parallelizable Algorithms for Non-Monotone Submodular Maximization with Size Constraint
by: Chen, Yixin, et al.
Published: (2020)

FedSPDnet: Geometry-Aware Federated Deep Learning with SPDnet
by: Pautrel, Thibault, et al.
Published: (2026)

Mini-Hes: A Parallelizable Second-order Latent Factor Analysis Model
by: Wang, Jialiang, et al.
Published: (2024)

A Near-optimal, Scalable and Parallelizable Framework for Stochastic Bandits Robust to Adversarial Corruptions and Beyond
by: Hu, Zicheng, et al.
Published: (2025)

How to craft a deep reinforcement learning policy for wind farm flow control
by: Kadoche, Elie, et al.
Published: (2025)

Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators
by: Baumeister, Fabian, et al.
Published: (2024)

Fair Reinforcement Learning Algorithm for PV Active Control in LV Distribution Networks
by: Vassallo, Maurizio, et al.
Published: (2024)

Tenplex: Dynamic Parallelism for Deep Learning using Parallelizable Tensor Collections
by: Wagenländer, Marcel, et al.
Published: (2023)

Intrinsic Bayesian Cramér-Rao Bound with an Application to Covariance Matrix Estimation
by: Bouchard, Florent, et al.
Published: (2023)

How noise affects memory in linear recurrent networks
by: Guan, JingChuan, et al.
Published: (2024)

ProSh: Probabilistic Shielding for Model-free Reinforcement Learning
by: Court, Edwin Hamel-De le, et al.
Published: (2025)

Adaptive control of recurrent neural networks using conceptors
by: Pourcel, Guillaume, et al.
Published: (2024)

Understanding Sample Efficiency in Predictive Coding
by: Oliviers, Gaspard, et al.
Published: (2026)

Using LLMs for Analyzing AIS Data
by: Merten, Gaspard, et al.
Published: (2025)