Saikat Chatterjee

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 105

Top Venues

Publications

Anubhab Ghosh, Antoine Honoré, Saikat Chatterjee
DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Learning Setup. IEEE Trans. Signal Process. 72 (2024)
Anubhab Ghosh, Yonina C. Eldar, Saikat Chatterjee
Data-driven Bayesian State Estimation with Compressed Measurement of Model-free Process using Semi-supervised Learning. CoRR (2024)
Sandipan Das, Bengt Boberg, Maurice F. Fallon, Saikat Chatterjee
IMU-based Online Multi-lidar Calibration. IV (2024)
Anubhab Ghosh, Mohamed Abdalmoaty, Saikat Chatterjee, Håkan Hjalmarsson
DeepBayes - An estimator for parameter estimation in stochastic nonlinear dynamical models. Autom. 159 (2024)
Sandipan Das, Ludvig af Klinteberg, Maurice F. Fallon, Saikat Chatterjee
Observability-Aware Online Multi-Lidar Extrinsic Calibration. IEEE Robotics Autom. Lett. 8 (5) (2023)
Ritumbra Manuvie, Saikat Chatterjee
Identifying and analysing toxic actors and communities on Facebook by employing network analysis. CoRR (2023)
Antoine Honoré, Anubhab Ghosh, Saikat Chatterjee
Compressed Sensing of Generative Sparse-Latent (GSL) Signals. EUSIPCO (2023)
Fredrik Cumlin, Christian Schüldt, Saikat Chatterjee
Latent-Based Neural Net for Non-Intrusive Speech Quality Assessment. EUSIPCO (2023)
Anubhab Ghosh, Antoine Honoré, Saikat Chatterjee
DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Bayesian Setup. EUSIPCO (2023)
Xinyu Liang, Fredrik Cumlin, Christian Schüldt, Saikat Chatterjee
DeePMOS: Deep Posterior Mean-Opinion-Score of Speech. INTERSPEECH (2023)
Antoine Honoré, Anubhab Ghosh, Saikat Chatterjee
Compressed Sensing of Generative Sparse-latent (GSL) Signals. CoRR (2023)
Sandipan Das, Navid Mahabadi, Maurice F. Fallon, Saikat Chatterjee
M-LIO: Multi-lidar, multi-IMU odometry with sensor dropout tolerance. IV (2023)
Saikat Chatterjee, Praphulla Koushik
Extension of Topological Groupoids and Hurewicz Morphisms. Appl. Categorical Struct. 31 (5) (2023)
Anubhab Ghosh, Antoine Honoré, Saikat Chatterjee
DANSE: Data-driven Non-linear State Estimation of Model-free Process in Unsupervised Learning Setup. CoRR (2023)
Ritumbra Manuvie, Saikat Chatterjee
Automated Sentiment and Hate Speech Analysis of Facebook Data by Employing Multilingual Transformer Models. CoRR (2023)
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
Decentralized learning of randomization-based neural networks with centralized equivalence. Appl. Soft Comput. 115 (2022)
Sandipan Das, Navid Mahabadi, Maurice F. Fallon, Saikat Chatterjee
M-LIO: Multi-lidar, multi-IMU odometry with sensor dropout tolerance. CoRR (2022)
Sandipan Das, Navid Mahabadi, Addi Djikic, Cesar Nassir, Saikat Chatterjee, Maurice F. Fallon
Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors. CoRR (2022)
Sandipan Das, Navid Mahabadi, Addi Djikic, Cesar Nassir, Saikat Chatterjee, Maurice F. Fallon
Extrinsic Calibration and Verification of Multiple Non-overlapping Field of View Lidar Sensors. ICRA (2022)
Fatemeh Arian, Mehdi Amini, Shayan Mostafaei, Kiara Rezaei-Kalantari, Atlas Haddadi Avval, Zahra Shahbazi, Kianosh Kasani, Ahmad Bitarafan-rajabi, Saikat Chatterjee, Mehrdad Oveisi, Isaac Shiri, Habib Zaidi
Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms. J. Digit. Imaging 35 (6) (2022)
Simei Yang, Debjyoti Bhattacharjee, Vinay B. Y. Kumar, Saikat Chatterjee, Sayandip De, Peter Debacker, Diederik Verkest, Arindam Mallik, Francky Catthoor
AERO: Design Space Exploration Framework for Resource-Constrained CNN Mapping on Tile-Based Accelerators. IEEE J. Emerg. Sel. Topics Circuits Syst. 12 (2) (2022)
Sandipan Das, Ludvig af Klinteberg, Maurice F. Fallon, Saikat Chatterjee
Observability-aware online multi-lidar extrinsic calibration. CoRR (2022)
Anubhab Ghosh, Mohamed Rasheed Abdalmoaty, Saikat Chatterjee, Håkan Hjalmarsson
DeepBayes - an estimator for parameter estimation in stochastic nonlinear dynamical models. CoRR (2022)
Pol Grau Jurado, Xinyue Liang, Saikat Chatterjee
Deterministic Transform Based Weight Matrices for Neural Networks. ICASSP (2022)
Anubhab Ghosh, Aleix Espuña Fontcuberta, Mohamed Rasheed-Hilmy Abdalmoaty, Saikat Chatterjee
Time-varying Normalizing Flow for Generative Modeling of Dynamical Signals. EUSIPCO (2022)
Sandipan Das, Alireza M. Javid, Prakash Borpatra Gohain, Yonina C. Eldar, Saikat Chatterjee
Neural Greedy Pursuit for Feature Selection. IJCNN (2022)
Sandipan Das, Navid Mahabadi, Saikat Chatterjee, Maurice F. Fallon
Multi-modal curb detection and filtering. CoRR (2022)
Sandipan Das, Alireza M. Javid, Prakash Borpatra Gohain, Yonina C. Eldar, Saikat Chatterjee
Neural Greedy Pursuit for Feature Selection. CoRR (2022)
Anubhab Ghosh, Antoine Honoré, Dong Liu, Gustav Eje Henter, Saikat Chatterjee
Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows. CoRR (2021)
Alireza M. Javid, Sandipan Das, Mikael Skoglund, Saikat Chatterjee
A ReLU Dense Layer to Improve the Performance of Neural Networks. ICASSP (2021)
Pol Grau Jurado, Xinyue Liang, Alireza M. Javid, Saikat Chatterjee
Use of Deterministic Transforms to Design Weight Matrices of a Neural Network. CoRR (2021)
Xinyue Liang, Mikael Skoglund, Saikat Chatterjee
Feature Reuse for a Randomization Based Neural Network. ICASSP (2021)
Anubhab Ghosh, Antoine Honoré, Dong Liu, Gustav Eje Henter, Saikat Chatterjee
Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with Explainability. CoRR (2021)
Helmer Nylén, Saikat Chatterjee, Sten Ternström
Detecting Signal Corruptions in Voice Recordings For Speech Therapy. ICASSP (2021)
Pol Grau Jurado, Xinyue Liang, Alireza M. Javid, Saikat Chatterjee
Use of Deterministic Transforms to Design Weight Matrices of a Neural Network. EUSIPCO (2021)
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
Asynchronous Decentralized Learning of Randomization-Based Neural Networks. IJCNN (2021)
Sajad Mehrizi, Saikat Chatterjee, Symeon Chatzinotas, Björn E. Ottersten
Online Spatiotemporal Popularity Learning via Variational Bayes for Cooperative Caching. IEEE Trans. Commun. 68 (11) (2020)
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning. CoRR (2020)
Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee
High-dimensional Neural Feature using Rectified Linear Unit and Random Matrix Instance. CoRR (2020)
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
Learning without Forgetting for Decentralized Neural Nets with Low Communication Overhead. EUSIPCO (2020)
Filip Wen-Fwu Tsai, Alireza M. Javid, Saikat Chatterjee
Design of a Non-negative Neural Network to Improve on NMF. EUSIPCO (2020)
Sandipan Das, Prakash B. Gohain, Alireza M. Javid, Yonina C. Eldar, Saikat Chatterjee
Statistical model-based evaluation of neural networks. CoRR (2020)
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
Asynchronous Decentralized Learning of a Neural Network. CoRR (2020)
Alireza M. Javid, Xinyue Liang, Arun Venkitaraman, Saikat Chatterjee
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University. CoRR (2020)
Anubhab Ghosh, Antoine Honoré, Dong Liu, Gustav Eje Henter, Saikat Chatterjee
Robust Classification Using Hidden Markov Models and Mixtures of Normalizing Flows. MLSP (2020)
Antoine Honoré, Dong Liu, David Forsberg, Karen Coste, Eric Herlenius, Saikat Chatterjee, Mikael Skoglund
Hidden Markov Models for Sepsis Detection in Preterm Infants. ICASSP (2020)
Zhijing Li, YangYang Lan, Saikat Chatterjee, Pargorn Puttapirat, Xiangrong Zhang, Chen Li
Dual sentence representation model integrating prior knowledge for bio-text-mining. BIBM (2020)
Arun Venkitaraman, Saikat Chatterjee, Bo Wahlberg
Recursive Prediction of Graph Signals With Incoming Nodes. ICASSP (2020)
Dong Liu, Antoine Honoré, Saikat Chatterjee, Lars K. Rasmussen
Powering Hidden Markov Model by Neural Network Based Generative Models. ECAI (2020)
Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee
High-dimensional neural feature design for layer-wise reduction of training cost. EURASIP J. Adv. Signal Process. 2020 (1) (2020)
Alireza M. Javid, Sandipan Das, Mikael Skoglund, Saikat Chatterjee
A ReLU Dense Layer to Improve the Performance of Neural Networks. CoRR (2020)
Alireza M. Javid, Xinyue Liang, Mikael Skoglund, Saikat Chatterjee
Adaptive Learning without Forgetting via Low-Complexity Convex Networks. EUSIPCO (2020)
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
A Low Complexity Decentralized Neural Net with Centralized Equivalence using Layer-wise Learning. IJCNN (2020)
Alireza M. Javid, Arun Venkitaraman, Mikael Skoglund, Saikat Chatterjee
High-Dimensional Neural Feature Using Rectified Linear Unit And Random Matrix Instance. ICASSP (2020)
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
Asynchrounous Decentralized Learning of a Neural Network. ICASSP (2020)
Arun Venkitaraman, Saikat Chatterjee, Peter Handel
Gaussian Processes Over Graphs. ICASSP (2020)
Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen
Neural Network based Explicit Mixture Models and Expectation-maximization based Learning. IJCNN (2020)
Arun Venkitaraman, Saikat Chatterjee, Bo Wahlberg
Recursive Prediction of Graph Signals with Incoming Nodes. CoRR (2019)
Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen
Neural Network based Explicit Mixture Models and Expectation-maximization based Learning. CoRR (2019)
Dong Liu, Nima N. Moghadam, Lars K. Rasmussen, Jinliang Huang, Saikat Chatterjee
α Belief Propagation as Fully Factorized Approximation. CoRR (2019)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Predicting Graph Signals Using Kernel Regression Where the Input Signal is Agnostic to a Graph. IEEE Trans. Signal Inf. Process. over Networks 5 (4) (2019)
Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen
Entropy-regularized Optimal Transport Generative Models. ICASSP (2019)
Arun Venkitaraman, Pascal Frossard, Saikat Chatterjee
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. ICASSP (2019)
Mostafa Sadeghi, Fateme Ghayem, Massoud Babaie-Zadeh, Saikat Chatterjee, Mikael Skoglund, Christian Jutten
LOSoft: ℓ0 Minimization via Soft Thresholding. EUSIPCO (2019)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
On Hilbert transform, analytic signal, and modulation analysis for signals over graphs. Signal Process. 156 (2019)
Dong Liu, Antoine Honoré, Saikat Chatterjee, Lars K. Rasmussen
Powering Hidden Markov Model by Neural Network based Generative Models. CoRR (2019)
Ahmed Zaki, Saikat Chatterjee
Convex Optimization Based Sparse Learning Over Networks. EUSIPCO (2019)
Antoine Honoré, Dong Liu, David Forsberg, Karen Coste, Eric Herlenius, Saikat Chatterjee, Mikael Skoglund
Hidden Markov Models for sepsis detection in preterm infants. CoRR (2019)
Dong Liu, Nima N. Moghadam, Lars K. Rasmussen, Jinliang Huang, Saikat Chatterjee
α Belief Propagation as Fully Factorized Approximation. GlobalSIP (2019)
Saikat Chatterjee, Alireza M. Javid, Mostafa Sadeghi, Shumpei Kikuta, Partha P. Mitra, Mikael Skoglund
SSFN: Self Size-estimating Feed-forward Network and Low Complexity Design. CoRR (2019)
Ahmed Zaki, Partha P. Mitra, Lars K. Rasmussen, Saikat Chatterjee
Estimate exchange over network is good for distributed hard thresholding pursuit. Signal Process. 156 (2019)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Gaussian Processes Over Graphs. CoRR (2018)
Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee
Distributed Large Neural Network with Centralized Equivalence. ICASSP (2018)
Arun Venkitaraman, Saikat Chatterjee, Peter Handel
Multi-Kernel Regression for Graph Signal Processing. ICASSP (2018)
Alireza M. Javid, Saikat Chatterjee, Mikael Skoglund
Mutual Information Preserving Analysis of a Single Layer Feedforward Network. ISWCS (2018)
Arun Venkitaraman, Pascal Frossard, Saikat Chatterjee
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise. CoRR (2018)
Fateme Ghayem, Mostafa Sadeghi, Massoud Babaie-Zadeh, Saikat Chatterjee, Mikael Skoglund, Christian Jutten
Sparse Signal Recovery Using Iterative Proximal Projection. IEEE Trans. Signal Process. 66 (4) (2018)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Multi-kernel Regression For Graph Signal Processing. CoRR (2018)
Ahmed Zaki, Arun Venkitaraman, Saikat Chatterjee, Lars Kildehoj Rasmussen
Greedy Sparse Learning Over Network. IEEE Trans. Signal Inf. Process. over Networks 4 (3) (2018)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Extreme Learning Machine for Graph Signal Processing. CoRR (2018)
Ahmed Zaki, Saikat Chatterjee, Partha P. Mitra, Lars K. Rasmussen
Locally Convex Sparse Learning over Networks. CoRR (2018)
Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen
Entropy-regularized Optimal Transport Generative Models. CoRR (2018)
Arun Venkitaraman, Alireza M. Javid, Saikat Chatterjee
R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network. CoRR (2018)
Arun Venkitaraman, Hermina Petric Maretic, Saikat Chatterjee, Pascal Frossard
Supervised Linear Regression for Graph Learning from Graph Signals. CoRR (2018)
Arun Venkitaraman, Saikat Chatterjee, Peter Handel
Extreme Learning Machine for Graph Signal Processing. EUSIPCO (2018)
Antoine Honoré, Veronica Siljehav, Saikat Chatterjee, Eric Herlenius
Large Neural Network Based Detection of Apnea, Bradycardia and Desaturation Events. CoRR (2017)
Martin Sundin, Arun Venkitaraman, Magnus Jansson, Saikat Chatterjee
A connectedness constraint for learning sparse graphs. EUSIPCO (2017)
Saikat Chatterjee, Alireza M. Javid, Mostafa Sadeghi, Partha P. Mitra, Mikael Skoglund
Progressive Learning for Systematic Design of Large Neural Networks. CoRR (2017)
Ahmed Zaki, Arun Venkitaraman, Saikat Chatterjee, Lars K. Rasmussen
Distributed greedy sparse learning over doubly stochastic networks. EUSIPCO (2017)
Ahmed Zaki, Saikat Chatterjee, Lars K. Rasmussen
Generalized fusion algorithm for compressive sampling reconstruction and RIP-based analysis. Signal Process. 139 (2017)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Kernel Regression for Signals over Graphs. CoRR (2017)
Kezhi Li, Martin Sundin, Cristian R. Rojas, Saikat Chatterjee, Magnus Jansson
Alternating strategies with internal ADMM for low-rank matrix reconstruction. Signal Process. 121 (2016)
Gaurav Fotedar, Aditya Gaonkar P., Saikat Chatterjee, Prasanta Kumar Ghosh
Automatic Recognition of Social Roles Using Long Term Role Transitions in Small Group Interactions. INTERSPEECH (2016)
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
Hilbert Transform, Analytic Signal, and Modulation Analysis for Graph Signal Processing. CoRR (2016)
Martin Sundin, Saikat Chatterjee, Magnus Jansson
Bayesian Cramer-Rao bounds for factorized model based low rank matrix reconstruction. EUSIPCO (2016)
Dennis Sundman, Saikat Chatterjee, Mikael Skoglund
Design and Analysis of a Greedy Pursuit for Distributed Compressed Sensing. IEEE Trans. Signal Process. 64 (11) (2016)
Martin Sundin, Cristian R. Rojas, Magnus Jansson, Saikat Chatterjee
Relevance Singular Vector Machine for Low-Rank Matrix Reconstruction. IEEE Trans. Signal Process. 64 (20) (2016)
Mikko Vehkaperä, Yoshiyuki Kabashima, Saikat Chatterjee
Analysis of Regularized LS Reconstruction and Random Matrix Ensembles in Compressed Sensing. IEEE Trans. Inf. Theory 62 (4) (2016)
Marten Vohrmann, Saikat Chatterjee, Sven Lütkemeier, Thorsten Jungeblut, Mario Porrmann, Ulrich Rückert
A 65 nm standard cell library for ultra low-power applications. ECCTD (2015)
Martin Sundin, Cristian R. Rojas, Magnus Jansson, Saikat Chatterjee
Bayesian Learning for Low-Rank matrix reconstruction. CoRR (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Saikat Chatterjee