An equivalence between high dimensional Bayes optimal inference and M-estimation. - Madhu Advani; Surya Ganguli (NIPS, 2016)

High-dimensional dynamics of generalization error in neural networks. - Madhu S. Advani; Andrew M. Saxe (CoRR, 2017)

On the Information Bottleneck Theory of Deep Learning. - Andrew M. Saxe; Yamini Bansal; Joel Dapello; Madhu Advani; Artemy Kolchinsky; Brendan D. Tracey; David D. Cox (ICLR (Poster), 2018)

Energy-entropy competition and the effectiveness of stochastic gradient descent in machine learning. - Yao Zhang; Andrew M. Saxe; Madhu S. Advani; Alpha A. Lee (CoRR, 2018)

Minnorm training: an algorithm for training over-parameterized deep neural networks. - Yamini Bansal; Madhu Advani; David D. Cox; Andrew M. Saxe (CoRR, 2018)

Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup. - Sebastian Goldt; Madhu Advani; Andrew M. Saxe; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2019)

Generalisation dynamics of online learning in over-parameterised neural networks. - Sebastian Goldt; Madhu S. Advani; Andrew M. Saxe; Florent Krzakala; Lenka Zdeborová (CoRR, 2019)

Dimensionality compression and expansion in Deep Neural Networks. - Stefano Recanatesi; Matthew Farrell; Madhu Advani; Timothy Moore; Guillaume Lajoie; Eric Shea-Brown (CoRR, 2019)

A new role for circuit expansion for learning in neural networks. - Julia Steinberg; Madhu Advani; Haim Sompolinsky (CoRR, 2020)

High-dimensional dynamics of generalization error in neural networks. - Madhu S. Advani; Andrew M. Saxe; Haim Sompolinsky (Neural Networks, 2020)

How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks. - Etai Littwin; Omid Saremi; Madhu Advani; Vimal Thilak; Preetum Nakkiran; Chen Huang 001; Joshua M. Susskind (NeurIPS, 2024)

Step-by-Step Diffusion: An Elementary Tutorial. - Preetum Nakkiran; Arwen Bradley; Hattie Zhou; Madhu Advani (Found. Trends Comput. Graph. Vis., 2025)