:: Library Catalog

Saved in:

Bibliographic Details
Main Authors:	Zheng, Caleb, Shlizerman, Eli
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2506.07975
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

R-FORCE: Robust Learning for Random Recurrent Neural Networks
by: Zheng, Yang, et al.
Published: (2020)

2ndMatch: Finetuning Pruned Diffusion Models via Second-Order Jacobian Matching
by: Zheng, Caleb, et al.
Published: (2025)

KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks
by: Hazelden, James, et al.
Published: (2025)

Spectral Pruning for Recurrent Neural Networks
by: Furuya, Takashi, et al.
Published: (2021)

SAVVY: Spatial Awareness via Audio-Visual LLMs through Seeing and Hearing
by: Chen, Mingfei, et al.
Published: (2025)

Neural Tangent Knowledge Distillation for Optical Convolutional Networks
by: Xiang, Jinlin, et al.
Published: (2025)

From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation
by: Su, Kun, et al.
Published: (2024)

Tell What You Hear From What You See -- Video to Audio Generation Through Text
by: Liu, Xiulong, et al.
Published: (2024)

Spectral Theory for Edge Pruning in Asynchronous Recurrent Graph Neural Networks
by: Bessone, Nicolas
Published: (2025)

Lattice-Based Pruning in Recurrent Neural Networks via Poset Modeling
by: Sengupta, Rakesh
Published: (2025)

RPNT: Robust Pre-trained Neural Transformer -- A Pathway for Generalized Motor Decoding
by: Fang, Hao, et al.
Published: (2026)

The Global Empirical NTK: Self-Referential Bias and Dimensionality of Gradient Descent Learning
by: Hazelden, James, et al.
Published: (2026)

SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding
by: Le, Trung, et al.
Published: (2025)

Multi-Objective Evolutionary Neural Architecture Search for Recurrent Neural Networks
by: Booysen, Reinhard, et al.
Published: (2024)

ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks
by: Hu, Wenhao, et al.
Published: (2025)

Information Consistent Pruning: How to Efficiently Search for Sparse Networks?
by: Gharatappeh, Soheil, et al.
Published: (2025)

Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons
by: Dufort-Labbé, Simon, et al.
Published: (2024)

Leveraging Intermediate Neural Collapse with Simplex ETFs for Efficient Deep Neural Networks
by: Liu, Emily
Published: (2024)

Joint Pruning and Channel-wise Mixed-Precision Quantization for Efficient Deep Neural Networks
by: Motetti, Beatrice Alessandra, et al.
Published: (2024)

Graph Expansion in Pruned Recurrent Neural Network Layers Preserve Performance
by: Kalra, Suryam Arnav, et al.
Published: (2024)

Energy-Efficient Spiking Recurrent Neural Network for Gesture Recognition on Embedded GPUs
by: Varposhti, Marzieh Hassanshahi, et al.
Published: (2024)

Pruning and Quantization Impact on Graph Neural Networks
by: Khedri, Khatoon, et al.
Published: (2025)

Mutual Information Preserving Neural Network Pruning
by: Westphal, Charles, et al.
Published: (2024)

Principled Pruning of Bayesian Neural Networks through Variational Free Energy Minimization
by: Beckers, Jim, et al.
Published: (2022)

Leveraging Recurrent Neural Networks for Predicting Motor Movements from Primate Motor Cortex Neural Recordings
by: Wang, Yuanxi, et al.
Published: (2024)

Investigating Sparsity in Recurrent Neural Networks
by: Darji, Harshil
Published: (2024)

Pruning Increases Orderedness in Recurrent Computation
by: Song, Yiding
Published: (2025)

Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure
by: Chu, Haoyu, et al.
Published: (2024)

Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression
by: Zhou, Longsheng, et al.
Published: (2026)

Constructive Lyapunov Functions via Topology-Preserving Neural Networks
by: Oh, Jaehong
Published: (2025)

Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks
by: Yun, Juyoung
Published: (2023)

Concurrent Training and Layer Pruning of Deep Neural Networks
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2024)

Random Search Neural Networks for Efficient and Expressive Graph Learning
by: Ito, Michael, et al.
Published: (2025)

An Uncertainty Principle for Linear Recurrent Neural Networks
by: François, Alexandre, et al.
Published: (2025)

Weight-Space Linear Recurrent Neural Networks
by: Nzoyem, Roussel Desmond, et al.
Published: (2025)

Generalization and Risk Bounds for Recurrent Neural Networks
by: Cheng, Xuewei, et al.
Published: (2024)

LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging
by: Kim, Jinuk, et al.
Published: (2024)

Quanvolutional Neural Networks for Spectrum Peak-Finding
by: Bischof, Lukas, et al.
Published: (2025)

Recurrent State Encoders for Efficient Neural Combinatorial Optimization
by: Dernedde, Tim, et al.
Published: (2025)

Shapley Pruning for Neural Network Compression
by: Adamczewski, Kamil, et al.
Published: (2024)