Summary of Evaluating Loss Landscapes From a Topology Perspective, by Tiankai Xie et al.
Evaluating Loss Landscapes from a Topology Perspectiveby Tiankai Xie, Caleb Geniesse, Jiaqing Chen, Yaoqing Yang,…
Evaluating Loss Landscapes from a Topology Perspectiveby Tiankai Xie, Caleb Geniesse, Jiaqing Chen, Yaoqing Yang,…
SAG-ViT: A Scale-Aware, High-Fidelity Patching Approach with Graph Attention for Vision Transformersby Shravan Venkatraman, Jaskaran…
Process-aware Human Activity Recognitionby Jiawei Zheng, Petros Papapanagiotou, Jacques D. Fleuriot, Jane HillstonFirst submitted to…
Least Squares Training of Quadratic Convolutional Neural Networks with Applications to System Theoryby Zachary Yetman…
Neural Conjugate Flows: Physics-informed architectures with flow structureby Arthur Bizzi, Lucas Nissenbaum, João M. PereiraFirst…
CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervisionby Aoi Ito, Kota Dohi, Yohei…
Deep Learning 2.0: Artificial Neurons That Matter – Reject Correlation, Embrace Orthogonalityby Taha BouhsineFirst submitted…
Tackling Polysemanticity with Neuron Embeddingsby Alex FooteFirst submitted to arxiv on: 12 Nov 2024CategoriesMain: Machine…
What Representational Similarity Measures Imply about Decodable Informationby Sarah E. Harvey, David Lipshutz, Alex H.…
Exploring Multi-Agent Reinforcement Learning for Unrelated Parallel Machine Schedulingby Maria Zampella, Urtzi Otamendi, Xabier Belaunzaran,…