Rudrasis Chakraborty
20 papers · 2015–2026 · 7 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (43) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🤝
Dynamic Duo
(13)
🧬
Topic Evolution
🏆
Keyword Champion
(2)
🧭
Keyword Pioneer
🔥
Unstoppable · Bronze
🗃️
Keyword Collector
(95)
⚡
Prolific Year · Productive
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(13)
Deep Learning
(10)
Core Methods
(8)
Optimization & Theory · Machine Learning
(7)
Computer Vision
(5)
Architectures
(5)
Artificial Intelligence
(4)
Mathematics & Optimization
(3)
Core AI
(3)
Domain-Specific
(3)
Learning Types
(3)
Models
(3)
Optimization & Theory · Deep Learning
(3)
Healthcare & Medicine
(2)
Analysis
(2)
Keywords
manifold learning
(3)
riemannian manifold
(3)
convolutional neural network
(2)
frechet mean
(2)
kernel methods
(2)
brain imaging
(2)
grassmann manifold
(2)
manifold-valued data
(2)
image reconstruction
(1)
medical imaging
(1)
self-attention mechanism
(1)
robust classification
(1)
image classification
(1)
hierarchical clustering
(1)
uncertainty quantification
(1)
computer vision
(1)
image generation
(1)
medical image analysis
(1)
hypothesis testing
(1)
efficient computing
(1)
Papers
ManifoldGD: Training-Free Hierarchical Manifold Guidance for Diffusion-Based Dataset Distillation
CVPR 2026
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets
CVPR 2022
Forward Operator Estimation in Generative Models with Kernel Transfer Operators
ICML 2022
On the Versatile Uses of Partial Distance Correlation in Deep Learning
ECCV 2022
Understanding Uncertainty Maps in Vision With Statistical Testing
CVPR 2022
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
NeurIPS 2021
A variational approximation for analyzing the dynamics of panel data
UAI 2021
Flow-based Generative Models for Learning Manifold to Manifold Mappings
AAAI 2021
Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention
AAAI 2021
Simpler Certified Radius Maximization by Propagating Covariances
CVPR 2021
Orthogonal Convolutional Neural Networks
CVPR 2020
Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data
ICCV 2019
Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains
ICCV 2019
A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices
NeurIPS 2018
A Geometric Framework for Statistical Analysis of Trajectories With Distinct Temporal Spans
ICCV 2017
Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning
CVPR 2017
Sparse Exact PGA on Riemannian Manifolds
ICCV 2017
An Efficient Exact-PGA Algorithm for Constant Curvature Manifolds
CVPR 2016
A Nonlinear Regression Technique for Manifold Valued Data With Applications to Medical Image Analysis
CVPR 2016
Recursive Frechet Mean Computation on the Grassmannian and its Applications to Computer Vision
ICCV 2015