Hadi Daneshmand

447 total citations
8 papers, 96 citations indexed

About

Hadi Daneshmand is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Statistics and Probability. According to data from OpenAlex, Hadi Daneshmand has authored 8 papers receiving a total of 96 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Statistical and Nonlinear Physics and 3 papers in Statistics and Probability. Recurrent topics in Hadi Daneshmand's work include Markov Chains and Monte Carlo Methods (3 papers), Stochastic Gradient Optimization Techniques (3 papers) and Complex Network Analysis Techniques (2 papers). Hadi Daneshmand is often cited by papers focused on Markov Chains and Monte Carlo Methods (3 papers), Stochastic Gradient Optimization Techniques (3 papers) and Complex Network Analysis Techniques (2 papers). Hadi Daneshmand collaborates with scholars based in Switzerland, United States and Germany. Hadi Daneshmand's co-authors include Thomas Hofmann, Aurélien Lucchi, Manuel Gomez-Rodriguez, Le Song, Bernhard Schoelkopf, Jonas Köhler, Bernhard Schölkopf, Francis Bach and Klaus Neymeyr and has published in prestigious journals such as Journal of Machine Learning Research, Repository for Publications and Research Data (ETH Zurich) and arXiv (Cornell University).

In The Last Decade

Hadi Daneshmand

8 papers receiving 94 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hadi Daneshmand Switzerland 7 55 40 20 7 7 8 96
Madhav Nimishakavi India 5 66 1.2× 39 1.0× 32 1.6× 5 0.7× 10 1.4× 7 99
Nicolas Flammarion United States 4 50 0.9× 9 0.2× 16 0.8× 12 1.7× 8 1.1× 14 85
Joshua V. Dillon United States 8 145 2.6× 12 0.3× 77 3.9× 8 1.1× 4 0.6× 9 205
Xiyu Zhai United States 5 78 1.4× 11 0.3× 25 1.3× 3 0.4× 4 0.6× 5 95
Christopher Fifty United States 2 100 1.8× 33 0.8× 28 1.4× 9 1.3× 5 0.7× 2 117
Mohammad Emtiyaz Khan Switzerland 9 124 2.3× 6 0.1× 24 1.2× 4 0.6× 6 0.9× 20 164
Su-In Lee United States 3 95 1.7× 8 0.2× 41 2.0× 6 0.9× 2 0.3× 3 150
Keyulu Xu United States 5 173 3.1× 46 1.1× 53 2.6× 9 1.3× 7 1.0× 8 190
Naganand Yadati India 6 152 2.8× 41 1.0× 115 5.8× 5 0.7× 11 1.6× 8 200

Countries citing papers authored by Hadi Daneshmand

Since Specialization
Citations

This map shows the geographic impact of Hadi Daneshmand'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 Hadi Daneshmand with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hadi Daneshmand more than expected).

Fields of papers citing papers by Hadi Daneshmand

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hadi Daneshmand. 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 Hadi Daneshmand. The network helps show where Hadi Daneshmand may publish in the future.

Co-authorship network of co-authors of Hadi Daneshmand

This figure shows the co-authorship network connecting the top 25 collaborators of Hadi Daneshmand. A scholar is included among the top collaborators of Hadi Daneshmand 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 Hadi Daneshmand. Hadi Daneshmand is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Daneshmand, Hadi, Jonas Köhler, Francis Bach, Thomas Hofmann, & Aurélien Lucchi. (2020). Batch normalization provably avoids ranks collapse for randomly initialised deep networks. Neural Information Processing Systems. 33. 18387–18398. 8 indexed citations
2.
Daneshmand, Hadi, Jonas Köhler, Francis Bach, Thomas Hofmann, & Aurélien Lucchi. (2020). Theoretical Understanding of Batch-normalization: A Markov Chain Perspective.. 3 indexed citations
3.
Daneshmand, Hadi, et al.. (2019). Local Saddle Point Optimization: A Curvature Exploitation Approach. Repository for Publications and Research Data (ETH Zurich). 13 indexed citations
4.
Daneshmand, Hadi, Jonas Köhler, Aurélien Lucchi, & Thomas Hofmann. (2018). Escaping Saddles with Stochastic Gradients. International Conference on Machine Learning. 1155–1164. 6 indexed citations
5.
Köhler, Jonas, et al.. (2018). Towards a Theoretical Understanding of Batch Normalization.. 14 indexed citations
6.
Gomez-Rodriguez, Manuel, Le Song, Hadi Daneshmand, & Bernhard Schölkopf. (2016). Estimating diffusion networks: recovery conditions, sample complexity & soft-thresholding algorithm. Journal of Machine Learning Research. 17(1). 3092–3120. 14 indexed citations
7.
Daneshmand, Hadi, Aurélien Lucchi, & Thomas Hofmann. (2016). Starting Small -- Learning with Adaptive Sample Sizes. arXiv (Cornell University). 1463–1471. 7 indexed citations
8.
Daneshmand, Hadi, Manuel Gomez-Rodriguez, Le Song, & Bernhard Schoelkopf. (2014). Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm.. PubMed. 32(2). 793–801. 31 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Madhav Nimishakavi Breakdown of academic impact, for papers by Nicolas Flammarion Breakdown of academic impact, for papers by Joshua V. Dillon Breakdown of academic impact, for papers by Xiyu Zhai Breakdown of academic impact, for papers by Christopher Fifty Breakdown of academic impact, for papers by Mohammad Emtiyaz Khan Breakdown of academic impact, for papers by Su-In Lee Breakdown of academic impact, for papers by Keyulu Xu Breakdown of academic impact, for papers by Naganand Yadati
Rankless by CCL
2026