Sample Pages (Top 50 by confidence)
Thoughts on loss landscapes and why deep learning works
https://www.beren.io/2023-07-11-Loss-landscapes-and-understanding-deep-learning
1 user
Last: Jan 07, 2026
100% confidence
Learning & Symmetry Group: 1. Generalization and Symmetry
https://learningsymmetry.github.io/posts/generalization_and_symmetry
1 user
Last: Jan 07, 2026
100% confidence
1.17. Neural network models (supervised) — scikit-learn 1.7.2 documentation
https://scikit-learn.org/stable/modules/neural_networks_supervised.html
1 user
Last: Jan 07, 2026
100% confidence
Early stopping - Wikipedia
https://en.wikipedia.org/wiki/Early_stopping
1 user
Last: Jan 07, 2026
100% confidence
Kolmogorov-Arnold Network is just an MLP
https://www.reddit.com/r/MachineLearning/comments/1clcu5i/d_kolmogorovarnold_net...
1 user
Last: Jan 07, 2026
100% confidence
Residual Networks (ResNet) - Deep Learning
https://www.geeksforgeeks.org/residual-networks-resnet-deep-learning
1 user
Last: Jan 07, 2026
100% confidence
Encapsulating Capsule Networks: Everything You Need To Know
https://gebob19.github.io/capsule-networks
1 user
Last: Jan 07, 2026
100% confidence
Capsule neural network
https://en.wikipedia.org/wiki/Capsule_neural_network
1 user
Last: Jan 07, 2026
100% confidence
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs | Pavel's Blog
https://izmailovpavel.github.io/curves_blogpost
1 user
Last: Jan 07, 2026
100% confidence
Learning Deep Low-Dimensional Models from High-Dimensional Data: From Theory to Practice
https://cvpr2024-tutorial-low-dim-models.github.io
1 user
Last: Jan 07, 2026
100% confidence
Computing Receptive Fields of Convolutional Neural Networks
https://distill.pub/2019/computing-receptive-fields
1 user
Last: Jan 07, 2026
100% confidence
Deep learning theory lecture notes
https://mjt.cs.illinois.edu/dlt
1 user
Last: Jan 07, 2026
100% confidence
GD’s Implicit Bias on Separable Data
https://xanderdavies.com/writing/implicit_bias_sgd/gd_imp_sep.html
1 user
Last: Jan 07, 2026
100% confidence
Landscape Connectivity of Low Cost Solutions for Multilayer Nets – Off the convex path
http://www.offconvex.org/2019/06/16/modeconnectivity
1 user
Last: Jan 07, 2026
100% confidence
Thoughts on Loss Landscapes and why Deep Learning works — LessWrong
https://www.lesswrong.com/posts/szXa8QgxjMypabJgN/thoughts-on-loss-landscapes-an...
1 user
Last: Jan 07, 2026
100% confidence
DSLT 1. The RLCT Measures the Effective Dimension of Neural Networks — LessWrong
https://www.lesswrong.com/posts/4eZtmwaqhAgdJQDEg/dslt-1-the-rlct-measures-the-e...
2 users
Last: Jan 09, 2026
100% confidence
DSLT 1. The RLCT Measures the Effective Dimension of Neural Networks — LessWrong
https://www.lesswrong.com/s/czrXjvCLsqGepybHC/p/4eZtmwaqhAgdJQDEg
2 users
Last: Jan 10, 2026
100% confidence
DSLT 2. Why Neural Networks obey Occam's Razor — LessWrong
https://www.lesswrong.com/s/czrXjvCLsqGepybHC/p/CZHwwDd7t9aYra5HN
1 user
Last: Jan 07, 2026
100% confidence
Generalized Low Rank Models
https://web.stanford.edu/~boyd/papers/pdf/glrm.pdf
1 user
Last: Jan 07, 2026
100% confidence
Visualizing Neural Networks with the Grand Tour
https://distill.pub/2020/grand-tour
1 user
Last: Jan 07, 2026
100% confidence
CS 230 - Convolutional Neural Networks Cheatsheet
https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-convolutional-neural-n...
1 user
Last: Jan 07, 2026
100% confidence
Gradient Hacking is extremely difficult.
https://www.beren.io/2023-01-21-gradient-hacking-extremely-difficult
2 users
Last: Jan 07, 2026
100% confidence
ADD / XOR / ROL: Some experiments to help me understand Neural Nets better, post 1 of N
https://addxorrol.blogspot.com/2024/07/some-experiments-to-help-me-understand.ht...
1 user
Last: Jan 07, 2026
100% confidence
Hill Space is All You Need
https://hillspace.justindujardin.com
1 user
Last: Jan 07, 2026
100% confidence
Greg Yang | Professional page
https://thegregyang.com
1 user
Last: Jan 07, 2026
100% confidence
Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization
https://www.pnas.org/doi/epdf/10.1073/pnas.0437847100
1 user
Last: Jan 07, 2026
100% confidence
Residual blocks — Building blocks of ResNet | by Sabyasachi Sahoo | Towards Data Science
https://towardsdatascience.com/residual-blocks-building-blocks-of-resnet-fd90ca1...
1 user
Last: Jan 07, 2026
100% confidence
jotterbach.github.io/content/posts/causal_noncausal_learning/2015-12-13-Causal_vs_Noncausal_Learning/
https://jotterbach.github.io/content/posts/causal_noncausal_learning/2015-12-13-...
1 user
Last: Jan 07, 2026
100% confidence
What Is Local Response Normalization In Convolutional Neural Networks – Perpetual Enigma
https://prateekvjoshi.com/2016/04/05/what-is-local-response-normalization-in-con...
1 user
Last: Jan 07, 2026
100% confidence
How does the inductive bias influence the generalization capability of neural networks? | ICLR Blogposts 2023
https://iclr-blogposts.github.io/2023/blog/2023/how-does-the-inductive-bias-infl...
1 user
Last: Jan 07, 2026
100% confidence
Understanding the Neural Tangent Kernel – EigenTales
https://www.eigentales.com/NTK
1 user
Last: Jan 07, 2026
100% confidence
Deep learning models are secretly (almost) linear
https://www.beren.io/2023-04-04-DL-models-are-secretly-linear
1 user
Last: Jan 07, 2026
100% confidence
L1 regularization: sparsity through singularities | Erik Jenner
https://ejenner.com/post/sparsity-singularities
1 user
Last: Jan 07, 2026
100% confidence
Conv Nets: A Modular Perspective - colah's blog
https://colah.github.io/posts/2014-07-Conv-Nets-Modular
1 user
Last: Jan 07, 2026
100% confidence
Interpreting logits: Sigmoid vs Softmax | Nandita Bhaskhar
https://web.stanford.edu/~nanbhas/blog/sigmoid-softmax
1 user
Last: Jan 07, 2026
100% confidence
Describing Double Descent with WeightWatcher – calculated | content
https://calculatedcontent.com/2024/03/01/describing-double-descent-with-weightwa...
1 user
Last: Jan 07, 2026
100% confidence
SIMPLIFYING NEURAL NETS BY DISCOVERING FLAT MINIMA
https://proceedings.neurips.cc/paper/1994/file/01882513d5fa7c329e940dda99b12147-...
1 user
Last: Jan 07, 2026
100% confidence
Visualizing Filters and Feature Maps in Convolutional Neural Networks
https://debuggercafe.com/visualizing-filters-and-feature-maps-in-convolutional-n...
1 user
Last: Jan 07, 2026
100% confidence
terminology - What exactly is a hypothesis space in machine learning? - Cross Validated
https://stats.stackexchange.com/questions/183989/what-exactly-is-a-hypothesis-sp...
1 user
Last: Jan 07, 2026
100% confidence
Regularization (mathematics) - Wikipedia
https://en.wikipedia.org/wiki/Regularization_(mathematics)
1 user
Last: Jan 07, 2026
100% confidence
A Gentle Introduction to the Rectified Linear Unit (ReLU) - MachineLearningMastery.com
https://machinelearningmastery.com/rectified-linear-activation-function-for-deep...
2 users
Last: Jan 07, 2026
100% confidence
Convolution Vs Correlation. Convolutional Neural Networks which are… | by Divyanshu Mishra | Towards Data Science
https://towardsdatascience.com/convolution-vs-correlation-af868b6b4fb5
1 user
Last: Jan 07, 2026
100% confidence
Why do we use ReLU in neural networks and how do we use it? - Cross Validated
https://stats.stackexchange.com/questions/226923/why-do-we-use-relu-in-neural-ne...
1 user
Last: Jan 07, 2026
100% confidence
Overview of Sparse Modeling | Chan`s Jupyter
https://goodboychan.github.io/machine_learning/2020/09/07/01-Overview-of-Sparse-...
1 user
Last: Jan 07, 2026
100% confidence