Summary of Mechanistic Interpretability Of Reinforcement Learning Agents, by Tristan Trim et al.
Mechanistic Interpretability of Reinforcement Learning Agentsby Tristan Trim, Triston GraystonFirst submitted to arxiv on: 30…
Summary of Generalizability Of Memorization Neural Networks, by Lijia Yu and Xiao-shan Gao and Lijun Zhang and Yibo Miao
Generalizability of Memorization Neural Networksby Lijia Yu, Xiao-Shan Gao, Lijun Zhang, Yibo MiaoFirst submitted to…
Summary of Advantages Of Neural Population Coding For Deep Learning, by Heiko Hoffmann
Advantages of Neural Population Coding for Deep Learningby Heiko HoffmannFirst submitted to arxiv on: 1…
Summary of A Kan-based Interpretable Framework For Process-informed Prediction Of Global Warming Potential, by Jaewook Lee et al.
A KAN-based Interpretable Framework for Process-Informed Prediction of Global Warming Potentialby Jaewook Lee, Xinyang Sun,…
Summary of Efficient Model Compression For Bayesian Neural Networks, by Diptarka Saha et al.
Efficient Model Compression for Bayesian Neural Networksby Diptarka Saha, Zihe Liu, Feng LiangFirst submitted to…
Summary of How Many Classifiers Do We Need?, by Hyunsuk Kim et al.
How many classifiers do we need?by Hyunsuk Kim, Liam Hodgkinson, Ryan Theisen, Michael W. MahoneyFirst…
Summary of Deep Learning Through a Telescoping Lens: a Simple Model Provides Empirical Insights on Grokking, Gradient Boosting & Beyond, by Alan Jeffares et al.
Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient…
Summary of Lagrangian Neural Networks For Nonholonomic Mechanics, by Viviana Alejandra Diaz et al.
Lagrangian neural networks for nonholonomic mechanicsby Viviana Alejandra Diaz, Leandro Martin Salomone, Marcela ZuccalliFirst submitted…
Summary of Learning Local Discrete Features in Explainable-by-design Convolutional Neural Networks, by Pantelis I. Kaplanoglou et al.
Learning local discrete features in explainable-by-design convolutional neural networksby Pantelis I. Kaplanoglou, Konstantinos DiamantarasFirst submitted…
Summary of The Importance Of Being Scalable: Improving the Speed and Accuracy Of Neural Network Interatomic Potentials Across Chemical Domains, by Eric Qu et al.
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials…