Rudrasis Chakraborty

77 papers A* 17A 2B 1Journal 42Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Pooling: Matching for Robust Generalization under Data Heterogeneity. CoRR Ayush Roy, Rudrasis Chakraborty, Lav R. Varshney, Vishnu Suresh Lokhande
2026	J	`jnl`	ManifoldGD: Training-Free Hierarchical Manifold Guidance for Diffusion-Based Dataset Distillation. CoRR Ayush Roy, Wei-Yang Alex Lee, Rudrasis Chakraborty, Vishnu Suresh Lokhande
2025	J	`jnl`	FoGE: Fock Space inspired encoding for graph prompting. CoRR Sotirios Panagiotis Chytas, Rudrasis Chakraborty, Vikas Singh
2024	J	`jnl`	Variational Sampling of Temporal Trajectories. CoRR Jurijs Nazarovs, Zhichun Huang, Xingjian Zhen, Sourav Pal, Rudrasis Chakraborty, Vikas Singh
2022	A*	`conf`	Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. CVPR Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh
2022	J	`jnl`	Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. CoRR Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh
2022	A*	`conf`	Forward Operator Estimation in Generative Models with Kernel Transfer Operators. ICML Zhichun Huang, Rudrasis Chakraborty, Vikas Singh
2022	J	`jnl`	ManifoldNet: A Deep Neural Network for Manifold-Valued Data With Applications. IEEE Trans. Pattern Anal. Mach. Intell. Rudrasis Chakraborty, Jose Bouza, Jonathan H. Manton, Baba C. Vemuri
2022	J	`jnl`	Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data. CoRR Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, Sathya N. Ravi, Vikas Singh
2022	—	`conf`	On the Versatile Uses of Partial Distance Correlation in Deep Learning. ECCV (26) Xingjian Zhen, Zihang Meng, Rudrasis Chakraborty, Vikas Singh
2022	J	`jnl`	On the Versatile Uses of Partial Distance Correlation in Deep Learning. CoRR Xingjian Zhen, Zihang Meng, Rudrasis Chakraborty, Vikas Singh
2022	J	`jnl`	SurReal: Complex-Valued Learning as Principled Transformations on a Scaling and Rotation Manifold. IEEE Trans. Neural Networks Learn. Syst. Rudrasis Chakraborty, Yifei Xing, Stella X. Yu
2022	J	`jnl`	Transformer for 3D Point Clouds. IEEE Trans. Pattern Anal. Mach. Intell. Jiayun Wang, Rudrasis Chakraborty, Stella X. Yu
2022	A*	`conf`	Understanding Uncertainty Maps in Vision with Statistical Testing. CVPR Jurijs Nazarovs, Zhichun Huang, Songwong Tasneeyapant, Rudrasis Chakraborty, Vikas Singh
2022	J	`jnl`	VolterraNet: A Higher Order Convolutional Network With Group Equivariance for Homogeneous Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. Monami Banerjee, Rudrasis Chakraborty, Jose Bouza, Baba C. Vemuri
2021	A	`conf`	A variational approximation for analyzing the dynamics of panel data. UAI Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant, Sathya N. Ravi, Vikas Singh
2021	A*	`conf`	An Online Riemannian PCA for Stochastic Canonical Correlation Analysis. NeurIPS Zihang Meng, Rudrasis Chakraborty, Vikas Singh
2021	J	`jnl`	An Online Riemannian PCA for Stochastic Canonical Correlation Analysis. CoRR Zihang Meng, Rudrasis Chakraborty, Vikas Singh
2021	A*	`conf`	Flow-based Generative Models for Learning Manifold to Manifold Mappings. AAAI Xingjian Zhen, Rudrasis Chakraborty, Liu Yang, Vikas Singh
2021	J	`jnl`	Forward Operator Estimation in Generative Models with Kernel Transfer Operators. CoRR Zhichun Huang, Rudrasis Chakraborty, Vikas Singh
2021	J	`jnl`	Intrinsic Grassmann Averages for Online Linear, Robust and Nonlinear Subspace Learning. IEEE Trans. Pattern Anal. Mach. Intell. Rudrasis Chakraborty, Liu Yang, Søren Hauberg, Baba C. Vemuri
2021	J	`jnl`	Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention. CoRR Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh
2021	A*	`conf`	Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention. AAAI Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh
2021	A*	`conf`	Simpler Certified Radius Maximization by Propagating Covariances. CVPR Xingjian Zhen, Rudrasis Chakraborty, Vikas Singh
2021	J	`jnl`	Simpler Certified Radius Maximization by Propagating Covariances. CoRR Xingjian Zhen, Rudrasis Chakraborty, Vikas Singh
2021	J	`jnl`	VolterraNet: A higher order convolutional network with group equivariance for homogeneous manifolds. CoRR Monami Banerjee, Rudrasis Chakraborty, Jose Bouza, Baba C. Vemuri
2020	—	`conf`	A GMM Based Algorithm To Generate Point-Cloud And Its Application To Neuroimaging. ISBI Workshops Liu Yang, Rudrasis Chakraborty
2020	—	`conf`	An "Augmentation-Free" Rotation Invariant Classification Scheme on Point-Cloud and Its Application to Neuroimaging. ISBI Liu Yang, Rudrasis Chakraborty
2020	—	`conf`	C-SURE: Shrinkage Estimator and Prototype Classifier for Complex-Valued Deep Learning. CVPR Workshops Rudrasis Chakraborty, Yifei Xing, Minxuan Duan, Stella X. Yu
2020	J	`jnl`	C-SURE: Shrinkage Estimator and Prototype Classifier for Complex-Valued Deep Learning. CoRR Yifei Xing, Rudrasis Chakraborty, Minxuan Duan, Stella X. Yu
2020	J	`jnl`	Flow-based Generative Models for Learning Manifold to Manifold Mappings. CoRR Xingjian Zhen, Rudrasis Chakraborty, Liu Yang, Vikas Singh
2020	J	`jnl`	ManifoldNorm: Extending normalizations on Riemannian Manifolds. CoRR Rudrasis Chakraborty
2020	A*	`conf`	Orthogonal Convolutional Neural Networks. CVPR Jiayun Wang, Yubei Chen, Rudrasis Chakraborty, Stella X. Yu
2019	—	`conf`	A Deep Neural Network for Manifold-Valued Data with Applications to Neuroimaging. IPMI Rudrasis Chakraborty, Jose Bouza, Jonathan H. Manton, Baba C. Vemuri
2019	J	`jnl`	A GMM based algorithm to generate point-cloud and its application to neuroimaging. CoRR Liu Yang, Rudrasis Chakraborty
2019	J	`jnl`	An "augmentation-free" rotation invariant classification scheme on point-cloud and its application to neuroimaging. CoRR Liu Yang, Rudrasis Chakraborty
2019	—	`conf`	DMR-CNN: A CNN Tailored For DMR Scans With Applications To PD Classification. ISBI Monami Banerjee, Rudrasis Chakraborty, Derek B. Archer, David E. Vaillancourt, Baba C. Vemuri
2019	A*	`conf`	Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data. ICCV Rudrasis Chakraborty, Xingjian Zhen, Nicholas Vogt, Barbara B. Bendlin, Vikas Singh
2019	J	`jnl`	Dilated Convolutional Neural Networks for Sequential Manifold-valued Data. CoRR Xingjian Zhen, Rudrasis Chakraborty, Nicholas Vogt, Barbara B. Bendlin, Vikas Singh
2019	J	`jnl`	Orthogonal Convolutional Neural Networks. CoRR Jiayun Wang, Yubei Chen, Rudrasis Chakraborty, Stella X. Yu
2019	J	`jnl`	POIRot: A rotation invariant omni-directional pointnet. CoRR Liu Yang, Rudrasis Chakraborty, Stella X. Yu
2019	A*	`conf`	Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains. ICCV Ronak Mehta, Rudrasis Chakraborty, Vikas Singh, Yunyang Xiong
2019	J	`jnl`	Spatial Transformer for 3D Points. CoRR Jiayun Wang, Rudrasis Chakraborty, Stella X. Yu
2019	—	`conf`	Sur-Real: Frechet Mean and Distance Transform for Complex-Valued Deep Learning. CVPR Workshops Rudrasis Chakraborty, Jiayun Wang, Stella X. Yu
2019	J	`jnl`	SurReal: Fréchet Mean and Distance Transform for Complex-Valued Deep Learning. CoRR Rudrasis Chakraborty, Jiayun Wang, Stella X. Yu
2019	J	`jnl`	Surreal: Complex-Valued Deep Learning as Principled Transformations on a Rotational Lie Group. CoRR Rudrasis Chakraborty, Yifei Xing, Stella X. Yu
2019	—	`conf`	Visual Similarity from Optimizing Feature and Memory On A Hypersphere. CVPR Workshops Xinlei Pan, Rudrasis Chakraborty, Stella X. Yu
2018	—	`conf`	A Mixture Model for Aggregation of Multiple Pre-Trained Weak Classifiers. CVPR Workshops Rudrasis Chakraborty, Chun-Hao Yang, Baba C. Vemuri
2018	A*	`conf`	A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices. NeurIPS Rudrasis Chakraborty, Chun-Hao Yang, Xingjian Zhen, Monami Banerjee, Derek B. Archer, David E. Vaillancourt, Vikas Singh, Baba C. Vemuri
2018	J	`jnl`	A mixture model for aggregation of multiple pre-trained weak classifiers. CoRR Rudrasis Chakraborty, Chun-Hao Yang, Baba C. Vemuri
2018	J	`jnl`	Dictionary Learning and Sparse Coding on Statistical Manifolds. CoRR Rudrasis Chakraborty, Monami Banerjee, Baba C. Vemuri
2018	—	`conf`	Generative Adversarial Network based Autoencoder: Application to Fault Detection Problem for Closed Loop Dynamical Systems. DX@Safeprocess Indrasis Chakraborty, Rudrasis Chakraborty, Draguna L. Vrabie
2018	J	`jnl`	Generative Adversarial Network based Autoencoder: Application to fault detection problem for closed loop dynamical systems. CoRR Indrasis Chakraborty, Rudrasis Chakraborty, Draguna L. Vrabie
2018	J	`jnl`	H-CNNs: Convolutional Neural Networks for Riemannian Homogeneous Spaces. CoRR Rudrasis Chakraborty, Monami Banerjee, Baba C. Vemuri
2018	J	`jnl`	ManifoldNet: A Deep Network Framework for Manifold-valued Data. CoRR Rudrasis Chakraborty, Jose Bouza, Jonathan H. Manton, Baba C. Vemuri
2018	J	`jnl`	Statistical Recurrent Models on Manifold valued Data. CoRR Rudrasis Chakraborty, Chun-Hao Yang, Xingjian Zhen, Monami Banerjee, Derek B. Archer, David E. Vaillancourt, Vikas Singh, Baba C. Vemuri
2017	A*	`conf`	A Geometric Framework for Statistical Analysis of Trajectories with Distinct Temporal Spans. ICCV Rudrasis Chakraborty, Vikas Singh, Nagesh Adluru, Baba C. Vemuri
2017	A*	`conf`	Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning. CVPR Rudrasis Chakraborty, Søren Hauberg, Baba C. Vemuri
2017	J	`jnl`	Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning. CoRR Rudrasis Chakraborty, Søren Hauberg, Baba C. Vemuri
2017	A*	`conf`	Sparse Exact PGA on Riemannian Manifolds. ICCV Monami Banerjee, Rudrasis Chakraborty, Baba C. Vemuri
2017	B	`conf`	Statistical analysis of longitudinal data and applications to neuro-imaging. ICIP Rudrasis Chakraborty, Baba C. Vemuri
2017	J	`jnl`	Statistics on the (compact) Stiefel manifold: Theory and Applications. CoRR Rudrasis Chakraborty, Baba C. Vemuri
2017	—	`conf`	Statistics on the space of trajectories for longitudinal data analysis. ISBI Rudrasis Chakraborty, Monami Banerjee, Baba C. Vemuri
2016	A*	`conf`	A Nonlinear Regression Technique for Manifold Valued Data with Applications to Medical Image Analysis. CVPR Monami Banerjee, Rudrasis Chakraborty, Edward Ofori, Michael S. Okun, David E. Vaillancourt, Baba C. Vemuri
2016	A*	`conf`	An Efficient Exact-PGA Algorithm for Constant Curvature Manifolds. CVPR Rudrasis Chakraborty, Dohyung Seo, Baba C. Vemuri
2016	J	`jnl`	An efficient Exact-PGA algorithm for constant curvature manifolds. CoRR Rudrasis Chakraborty, Dohyung Seo, Baba C. Vemuri
2015	J	`jnl`	Feature Selection Using a Neural Framework With Controlled Redundancy. IEEE Trans. Neural Networks Learn. Syst. Rudrasis Chakraborty, Nikhil R. Pal
2015	—	`conf`	Nonlinear Regression on Riemannian Manifolds and Its Applications to Neuro-Image Analysis. MICCAI (1) Monami Banerjee, Rudrasis Chakraborty, Edward Ofori, David E. Vaillancourt, Baba C. Vemuri
2015	J	`jnl`	Perceptual feature-based song genre classification using RANSAC. Int. J. Comput. Intell. Stud. Arijit Ghosal, Rudrasis Chakraborty, Bibhas Chandra Dhara, Sanjoy Kumar Saha
2015	J	`jnl`	Priority based ∈ dominance: A new measure in multiobjective optimization. Inf. Sci. Sanghamitra Bandyopadhyay, Rudrasis Chakraborty, Ujjwal Maulik
2015	A*	`conf`	Recursive Fréchet Mean Computation on the Grassmannian and Its Applications to Computer Vision. ICCV Rudrasis Chakraborty, Baba C. Vemuri
2014	J	`jnl`	Sensor (Group Feature) Selection with Controlled Redundancy in a Connectionist Framework. Int. J. Neural Syst. Rudrasis Chakraborty, Chin-Teng Lin, Nikhil R. Pal
2013	—	`conf`	Genre-Based Classification of Song Using Perceptual Features. ICACNI Arijit Ghosal, Rudrasis Chakraborty, Bibhas Chandra Dhara, Sanjoy Kumar Saha
2013	J	`jnl`	Incorporating ϵ-dominance in AMOSA: Application to multiobjective 0/1 knapsack problem and clustering gene expression data. Appl. Soft Comput. Sanghamitra Bandyopadhyay, Ujjwal Maulik, Rudrasis Chakraborty
2012	A	`conf`	Segmenting web-domains and hashtags using length specific models. CIKM Sriram Srinivasan, Sourangshu Bhattacharya, Rudrasis Chakraborty
2012	—	`conf`	Song/instrumental classification using spectrogram based contextual features. CUBE Arijit Ghosal, Rudrasis Chakraborty, Bibhas Chandra Dhara, Sanjoy Kumar Saha
2011	—	`conf`	Song Classification: Classical and Non-classical Discrimination Using MFCC Co-occurrence Based Features. FGIT-SIP Arijit Ghosal, Rudrasis Chakraborty, Bibhas Chandra Dhara, Sanjoy Kumar Saha