Madhu Advani

664 total citations
9 papers, 159 citations indexed

About

Madhu Advani is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Cognitive Neuroscience. According to data from OpenAlex, Madhu Advani has authored 9 papers receiving a total of 159 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 2 papers in Statistical and Nonlinear Physics and 2 papers in Cognitive Neuroscience. Recurrent topics in Madhu Advani's work include Neural Networks and Applications (3 papers), Stochastic Gradient Optimization Techniques (3 papers) and Neural dynamics and brain function (2 papers). Madhu Advani is often cited by papers focused on Neural Networks and Applications (3 papers), Stochastic Gradient Optimization Techniques (3 papers) and Neural dynamics and brain function (2 papers). Madhu Advani collaborates with scholars based in United States, United Kingdom and Israel. Madhu Advani's co-authors include Andrew Saxe, Pankaj Mehta, Guy Bunin, Yao Zhang, Alpha A. Lee, James E. Fitzgerald, Nelson Spruston, Weinan Sun, Brendan Tracey and Artemy Kolchinsky and has published in prestigious journals such as Nature Neuroscience, PLoS ONE and Molecular Physics.

In The Last Decade

Madhu Advani

8 papers receiving 156 citations

Peers

Countries citing papers authored by Madhu Advani

Since Specialization

Citations

This map shows the geographic impact of Madhu Advani's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Madhu Advani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Madhu Advani more than expected).

Fields of papers citing papers by Madhu Advani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Madhu Advani. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Madhu Advani. The network helps show where Madhu Advani may publish in the future.

Co-authorship network of co-authors of Madhu Advani

This figure shows the co-authorship network connecting the top 25 collaborators of Madhu Advani. A scholar is included among the top collaborators of Madhu Advani based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Madhu Advani. Madhu Advani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

#	Work	Indexed citations
1	Organizing memories for generalization in complementary learning systems 2023 ·Nature Neuroscience ·Weinan Sun, Madhu Advani, Nelson Spruston, Andrew Saxe, James E. Fitzgerald	29
2	New role for circuit expansion for learning in neural networks 2021 ·Physical review. E ·Julia Steinberg, Madhu Advani, Haim Sompolinsky	1
3	Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup 2019 ·arXiv (Cornell University) ·Sebastian Goldt, Madhu Advani, Andrew Saxe, Florent Krząkała, Lenka Zdeborová	9
4	On the information bottleneck theory of deep learning* 2019 ·Journal of Statistical Mechanics Theory and Experiment ·Andrew Saxe, Yamini Bansal, (unknown), Madhu Advani, Artemy Kolchinsky, Brendan Tracey, David Cox	35
5	Statistical physics of community ecology: a cavity solution to MacArthur’s consumer resource model 2018 ·Journal of Statistical Mechanics Theory and Experiment ·Madhu Advani, Guy Bunin, Pankaj Mehta	48
6	Learning Dynamics of Deep Networks Admit Low-Rank Tensor Descriptions 2018 ·(unknown), Alex H. Williams, Madhu Advani, Andrew Saxe, Surya Ganguli	0
7	Energy–entropy competition and the effectiveness of stochastic gradient descent in machine learning 2018 ·Molecular Physics ·Yao Zhang, Andrew Saxe, Madhu Advani, Alpha A. Lee	30
8	Position and orientation inference via on-board triangulation 2017 ·PLoS ONE ·Madhu Advani, Daniel S. Weile	2
9	An equivalence between high dimensional Bayes optimal inference and M-estimation 2016 ·Neural Information Processing Systems ·Madhu Advani, Surya Ganguli	5

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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