Dilip Krishnan

14.4k citations

41 papers · 5.0k indexed · 5 hit papers · h-index 21

Impact in

Computer Vision and Pattern Recognition top 0.2%
- Advanced Image Processing Techniques
- Image and Signal Denoising Methods
- Advanced Vision and Imaging
- Image Enhancement Techniques
- Advanced Neural Network Applications
Media Technology top 0.1%
- Image Processing Techniques and Applications
- Advanced Image Fusion Techniques

Papers in

Computational Mathematics 2
Computer Vision and Pattern Recognition 30
- Advanced Image Processing Techniques 11
- Advanced Vision and Imaging 8
- Image and Signal Denoising Methods 6
- Generative Adversarial Networks and Image Synthesis 5
- Image Enhancement Techniques 5

Co-authors: Rob Fergus Graham W. Taylor Matthew D. Zeiler David Dohan Konstantinos Bousmalis Dumitru Erhan Nathan Silberman David Eigen
Journals: ACM Transactions on Graphics (3 papers)Bioinformatics (2 papers)Advances in Computational Mathematics (1 paper)Radiology (1 paper)IEEE Transactions on Image Processing (1 paper)
Partner nations: United States Singapore United Kingdom

In The Last Decade

Dilip Krishnan

40 papers receiving 4.8k citations

Hit Papers

5 papers align trajectories log scale

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks 2017 · 942 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2017 Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks
2013 Restoring an Image Taken through a Window Covered with Dirt or Rain
2011 Blind deconvolution using a normalized sparsity measure
2010 Deconvolutional networks
2009 Neural Information Processing Systems

Peers

Countries citing papers authored by Dilip Krishnan

Since Specialization

Citations

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

Fields of papers citing papers by Dilip Krishnan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Dilip Krishnan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dilip Krishnan Line = papers co-authored together Dilip Krishnan links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	JESTR: Joint Embedding Space Technique for Ranking candidate molecules for the annotation of untargeted metabolomics data Bioinformatics ·Emma Nicholson, W.G. Dase, Dilip Krishnan, Soha Hassoun	2025	1
2	Driving Style Profiling Using Deep Autoencoders for Safety Applications in Urban and Highway Scenarios Dilip Krishnan, S. Srinivasan, Putri Aulia Natasya, Thomas Rolander, 喜佐子榊原, Salvatore Cafiso, Laura Galluccio, Giacomo Morabito, Giuseppina Pappalardo	2024	3
3	Learning Vision from Models Rivals Learning Vision from Data Yonglong Tian, Lijie Fan, Kaifeng Chen, Dina Katabi, Dilip Krishnan, Phillip Isola	2024	5
4	Scaling Laws of Synthetic Images for Model Training … for Now Lijie Fan, Kaifeng Chen, Dilip Krishnan, Dina Katabi, Phillip Isola, Yonglong Tian	2024	10
5	CSI: Contrastive data Stratification for Interaction prediction and its application to compound–protein interaction prediction Bioinformatics ·Emma Nicholson, Dilip Krishnan, Soha Hassoun	2023	3
6	Simplified Transfer Learning for Chest Radiography Models Using Less Data Radiology ·Biji Wong, Christina Chen, Mahmoud Darwich, Maria Papatriantafyllou, QI Zheng-fang, Aaron Sarna, Bhamidimarri B.K. Karthik, Charles T. Lau, Sreenivasa Raju Kalidindi, Mozziyar Etemadi, Florencia Garcia-Vicente, David Melnick, Yun Liu, Krishnan Eswaran, Daniel Tse, Arik Alper, Dilip Krishnan, Shravya Shetty	2022	30
7	What Makes for Good Views for Contrastive Learning arXiv (Cornell University) ·Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola	2020	49
8	Fantastic Generalization Measures and Where to Find Them International Conference on Learning Representations ·Yiding Jiang, Behnam Neyshabur, Dilip Krishnan, Hossein Mobahi, Samy Bengio	2020	8
9	Adversarial Robustness through Local Linearization Neural Information Processing Systems ·Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli	2019	27
10	Predicting the Generalization Gap in Deep Networks with Margin Distributions International Conference on Learning Representations ·Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio	2018	7
11	Face Synthesis from Facial Identity Features. arXiv (Cornell University) ·Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman	2017	7
12	Study of relationship between WBC count and Diabetic complications International Journal of Advances in Medicine ·Makbule Sönmezişik, Edward G. Ballweber, Dilip Krishnan	2017	8
13	Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan Hit paper breakdown →	2017	942
14	Shape and Illumination from Shading using the Generic Viewpoint Assumption DSpace@MIT (Massachusetts Institute of Technology) ·Daniel Zoran, Dilip Krishnan, José Bento, Bill Freeman	2014	11
15	Blind Deconvolution with Re-weighted Sparsity Promotion. arXiv (Cornell University) ·Dilip Krishnan, 张风坤, Rob Fergus	2013	10
16	Restoring an Image Taken through a Window Covered with Dirt or Rain David Eigen, Dilip Krishnan, Rob Fergus Hit paper breakdown →	2013	304
17	Multigrid and multilevel preconditioners for computational photography Dilip Krishnan, Richard Szeliski	2011	1
18	Fast Image Deconvolution using Hyper-Laplacian Priors Neural Information Processing Systems ·Dilip Krishnan, Rob Fergus Hit paper breakdown →	2009	800
19	Dark flash photography ACM Transactions on Graphics ·Dilip Krishnan, Rob Fergus	2009	87
20	Video Restoration on a Multiple TMS320C40 System 一英斎芳艶, Ruiwei Dai, Dilip Krishnan	1996	3

About Dilip Krishnan

Dilip Krishnan is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Media Technology and Artificial Intelligence, having authored 41 papers that have together received 5.0k indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (11 papers), Advanced Vision and Imaging (8 papers), Sparse and Compressive Sensing Techniques (6 papers), Image and Signal Denoising Methods (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers), Computer Graphics and Visualization Techniques (5 papers), Image Enhancement Techniques (5 papers) and Image Processing Techniques and Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.8k citations), Media Technology (1.5k citations), Computer Graphics and Computer-Aided Design (154 citations), Artificial Intelligence (1.1k citations) and Computational Mechanics (498 citations). Dilip Krishnan has collaborated with scholars based in United States, Singapore and United Kingdom. Frequent co-authors include Rob Fergus, Graham W. Taylor, Matthew D. Zeiler, David Dohan, Konstantinos Bousmalis, Dumitru Erhan, Nathan Silberman, David Eigen, William T. Freeman and Richard Szeliski. Their work appears in journals such as ACM Transactions on Graphics, Bioinformatics, Advances in Computational Mathematics, Radiology and IEEE Transactions on Image Processing.

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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