Sayan Mukherjee

91 papers A* 7A 2C 1Journal 67Unranked 14
YearRankTypeTitle / Venue / Authors
2026 J jnl
Robust Predictive Uncertainty and Double Descent in Contaminated Bayesian Random Features.
CoRR
Michele Caprio, Katerina Papagiannouli, Siu Lun Chau, Sayan Mukherjee
2025 J jnl
A Sheaf-Theoretic Construction of Shape Space.
Found. Comput. Math.
Shreya Arya, Justin Curry, Sayan Mukherjee
2025 J jnl
Calibrated Bayesian Uncertainty in Random Feature Regression via Optimal Posterior Tempering.
Bull. Comput. Data Sci.
Sayan Mukherjee, Samuel I. Berchuck
2025 — conf
Developing PeACE: A Pedagogical Agent for Children's Emotions.
EC-TEL (2)
Tyler Colasante, Eric Roldán Roa, Doris Kristina Raave, Juan Carlos Ramos Martinez, Hongtao Li, Tina Malti, Sayan Mukherjee
2025 A* conf
Higher Order Bipartiteness vs Bi-Partitioning in Simplicial Complexes.
SoCG
Marzieh Eidi, Sayan Mukherjee
2024 J jnl
Approximately Optimal Search on a Higher-dimensional Sliding Puzzle.
CoRR
Nono S. C. Merleau, Miguel O'Malley, Érika Roldán, Sayan Mukherjee
2024 — conf
Play My Math: First Development Cycle of an EdTech Tool Supporting the Teaching and Learning of Fractions Through Music in Algebraic Notation.
EC-TEL (2)
Eric Roldán Roa, Erika Berenice Roldan-Roa, Doris Kristina Raave, Jo Van Herwegen, Nina Polytimou, Sayan Mukherjee, Tyler Colasante, Tina Malti, Julia Mori, Marcus Specht
2024 — conf
Play My Math: Second Development Cycle of an EdTech Tool Supporting the Teaching and Learning of Fractions Through Music in Algebraic Notation.
ICITL (2)
Eric Roldán Roa, Erika Berenice Roldan-Roa, Doris Kristina Raave, Jo Van Herwegen, Nina Polytimou, Sayan Mukherjee, Tyler Colasante, Tina Malti, Julia Mori
2024 J jnl
Representing fields without correspondences: the lifted Euler characteristic transform.
J. Appl. Comput. Topol.
Henry Kirveslahti, Sayan Mukherjee
2023 A* conf
Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression.
NeurIPS
Youngsoo Baek, Samuel Berchuck, Sayan Mukherjee
2023 J jnl
Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression.
CoRR
Youngsoo Baek, Samuel I. Berchuck, Sayan Mukherjee
2023 J jnl
Concentration Inequalities and Optimal Number of Layers for Stochastic Deep Neural Networks.
IEEE Access
Michele Caprio, Sayan Mukherjee
2023 J jnl
Ergodic theorems for dynamic imprecise probability kinematics.
Int. J. Approx. Reason.
Michele Caprio, Sayan Mukherjee
2023 J jnl
Global Optimality of Elman-type RNN in the Mean-Field Regime.
CoRR
Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee
2023 A* conf
Global optimality of Elman-type RNNs in the mean-field regime.
ICML
Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee
2023 J jnl
Portability of PCR-Bias Calibration in 16S Amplicon Sequencing Across Runs, Instruments and Primer Lots.
Bull. Comput. Data Sci.
Sayan Mukherjee
2022 J jnl
A Sheaf-Theoretic Construction of Shape Space.
CoRR
Shreya Arya, Justin Curry, Sayan Mukherjee
2022 J jnl
A topological data analytic approach for discovering biophysical signatures in protein dynamics.
PLoS Comput. Biol.
Wai-Shing Tang, Gabriel Monteiro da Silva, Henry Kirveslahti, Erin Skeens, Bibo Feng, Timothy Sudijono, Kevin K. Yang, Sayan Mukherjee, Brenda M. Rubenstein, Lorin Crawford
2022 J jnl
Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T Processes.
J. Mach. Learn. Res.
Justin D. Silverman, Kimberly Roche, Zachary C. Holmes, Lawrence A. David, Sayan Mukherjee
2022 J jnl
Concentration inequalities and optimal number of layers for stochastic deep neural networks.
CoRR
Michele Caprio, Sayan Mukherjee
2022 J jnl
Learning Subspaces of Different Dimensions.
J. Comput. Graph. Stat.
Brian St. Thomas, Kisung You, Lizhen Lin, Lek-Heng Lim, Sayan Mukherjee
2022 J jnl
Stanza-GLM: Calibrated Non-Gaussian State-Space Forecasting with Nonlinear Latent Dynamics.
Bull. Comput. Data Sci.
Sayan Mukherjee, George Buckle
2022 J jnl
The accuracy of absolute differential abundance analysis from relative count data.
PLoS Comput. Biol.
Kimberly Roche, Sayan Mukherjee
2021 J jnl
A Bayesian hierarchical model to estimate DNA methylation conservation in colorectal tumors.
Bioinform.
Kevin A. Murgas, Yanlin Ma, Lidea K. Shahidi, Sayan Mukherjee, Andrew S. Allen, Darryl Shibata, Marc D. Ryser
2021 J jnl
Accelerating Markov Random Field Inference with Uncertainty Quantification.
CoRR
Ramin Bashizade, Xiangyu Zhang, Sayan Mukherjee, Alvin R. Lebeck
2021 J jnl
Measuring and mitigating PCR bias in microbiota datasets.
PLoS Comput. Biol.
Justin D. Silverman, Rachael J. Bloom, Sharon Jiang, Heather K. Durand, Eric Dallow, Sayan Mukherjee, Lawrence A. David
2021 A* conf
Statistical robustness of Markov chain Monte Carlo accelerators.
ASPLOS
Xiangyu Zhang, Ramin Bashizade, Yicheng Wang, Sayan Mukherjee, Alvin R. Lebeck
2021 J jnl
Subspace Clustering through Sub-Clusters.
J. Mach. Learn. Res.
Weiwei Li, Jan Hannig, Sayan Mukherjee
2021 J jnl
The Geometry of Synchronization Problems and Learning Group Actions.
Discret. Comput. Geom.
Tingran Gao, Jacek Brodzki, Sayan Mukherjee
2021 J jnl
Tightening the Loop Between Specification and Computation: BCDS Year Two.
Bull. Comput. Data Sci.
Sayan Mukherjee
2021 J jnl
Towards Explainable Convolutional Features for Music Audio Modeling.
CoRR
Anna K. Yanchenko, Mohammadreza Soltani, Robert J. Ravier, Sayan Mukherjee, Vahid Tarokh
2021 J jnl
mvESS-Z: A Robust Multivariate Effective Sample Size for Degenerate and Quantized Markov Chains.
Bull. Comput. Data Sci.
Sayan Mukherjee
2020 J jnl
At the Intersection of Deep Sequential Model Framework and State-space Model Framework: Study on Option Pricing.
CoRR
Ziyang Ding, Sayan Mukherjee
2020 J jnl
Beyond Application End-Point Results: Quantifying Statistical Robustness of MCMC Accelerators.
CoRR
Xiangyu Zhang, Ramin Bashizade, Yicheng Wang, Cheng Lyu, Sayan Mukherjee, Alvin R. Lebeck
2020 J jnl
Cost-Optimal Reachability for Timed Automata with Diagonals via Zone Simulations.
Bull. Comput. Data Sci.
Sayan Mukherjee
2020 J jnl
Introducing the Bulletin of Computer and Data Sciences.
Bull. Comput. Data Sci.
Sayan Mukherjee
2020 J jnl
Stanza: A Nonlinear State Space Model for Probabilistic Inference in Non-Stationary Time Series.
CoRR
Anna K. Yanchenko, Sayan Mukherjee
2019 J jnl
A Case for Quantifying Statistical Robustness of Specialized Probabilistic AI Accelerators.
CoRR
Xiangyu Zhang, Sayan Mukherjee, Alvin R. Lebeck
2019 J jnl
Adaptive particle-based approximations of the Gibbs posterior for inverse problems.
CoRR
Zilong Zou, Sayan Mukherjee, Harbir Antil, Wilkins Aquino
2018 J jnl
Learning Integral Representations of Gaussian Processes.
CoRR
Zilong Tan, Sayan Mukherjee
2018 J jnl
Multiple testing with persistent homology.
CoRR
Mikael Vejdemo-Johansson, Sayan Mukherjee
2018 A conf
Scalable Algorithms for Learning High-Dimensional Linear Mixed Models.
UAI
Zilong Tan, Kimberly Roche, Xiang Zhou, Sayan Mukherjee
2018 J jnl
Scalable Algorithms for Learning High-Dimensional Linear Mixed Models.
CoRR
Zilong Tan, Kimberly Roche, Xiang Zhou, Sayan Mukherjee
2018 J jnl
Subspace Clustering through Sub-Clusters.
CoRR
Weiwei Li, Jan Hannig, Sayan Mukherjee
2017 J jnl
Adaptive Randomized Dimension Reduction on Massive Data.
J. Mach. Learn. Res.
Gregory Darnell, Stoyan Georgiev, Sayan Mukherjee, Barbara E. Engelhardt
2017 J jnl
Classical Music Composition Using State Space Models.
CoRR
Anna K. Yanchenko, Sayan Mukherjee
2017 J jnl
Efficient Learning of Graded Membership Models.
CoRR
Zilong Tan, Sayan Mukherjee
2017 A* conf
Partitioned Tensor Factorizations for Learning Mixed Membership Models.
ICML
Zilong Tan, Sayan Mukherjee
2016 J jnl
Bayesian group factor analysis with structured sparsity.
J. Mach. Learn. Res.
Shiwen Zhao, Chuan Gao, Sayan Mukherjee, Barbara E. Engelhardt
2016 J jnl
Fast moment estimation for generalized latent Dirichlet models.
CoRR
Shiwen Zhao, Barbara E. Engelhardt, Sayan Mukherjee, David B. Dunson
2016 J jnl
Random walks on simplicial complexes and harmonics.
Random Struct. Algorithms
Sayan Mukherjee, John Steenbergen
2016 J jnl
The Geometry of Synchronization Problems and Learning Group Actions.
CoRR
Tingran Gao, Jacek Brodzki, Sayan Mukherjee
2015 — conf
Contour trees of uncertain terrains.
SIGSPATIAL/GIS
Wuzhou Zhang, Pankaj K. Agarwal, Sayan Mukherjee
2015 J jnl
Cumulon: Matrix-Based Data Analytics in the Cloud with Spot Instances.
Proc. VLDB Endow.
Botong Huang, Nicholas W. D. Jarrett, Shivnath Babu, Sayan Mukherjee, Jun Yang
2015 — conf
The Information Geometry of Mirror Descent.
GSI
Garvesh Raskutti, Sayan Mukherjee
2015 J jnl
The Information Geometry of Mirror Descent.
IEEE Trans. Inf. Theory
Garvesh Raskutti, Sayan Mukherjee
2014 J jnl
A Cheeger-type inequality on simplicial complexes.
Adv. Appl. Math.
John Steenbergen, Caroline J. Klivans, Sayan Mukherjee
2014 J jnl
Cumulon: Cloud-Based Statistical Analysis from Users Perspective.
IEEE Data Eng. Bull.
Botong Huang, Nicholas W. D. Jarrett, Shivnath Babu, Sayan Mukherjee, Jun Yang
2014 J jnl
Fréchet Means for Distributions of Persistence Diagrams.
Discret. Comput. Geom.
Katharine Turner, Yuriy Mileyko, Sayan Mukherjee, John Harer
2013 J jnl
A comparative study of covariance selection models for the inference of gene regulatory networks.
J. Biomed. Informatics
Patrizia F. Stifanelli, Teresa Maria Creanza, Roberto Anglani, Vania C. Liuzzi, Sayan Mukherjee, Francesco P. Schena, Nicola Ancona
2013 J jnl
Genome-wide identification and predictive modeling of tissue-specific alternative polyadenylation.
Bioinform.
Dina Hafez, Ting Ni, Sayan Mukherjee, Jun Zhu, Uwe Ohler
2013 J jnl
Probabilistic Fréchet Means and Statistics on Vineyards.
CoRR
Elizabeth Munch, Paul Bendich, Katharine Turner, Sayan Mukherjee, Jonathan Mattingly, John Harer
2013 J jnl
The Information Geometry of Mirror Descent.
CoRR
Garvesh Raskutti, Sayan Mukherjee
2012 J jnl
A Cheeger-Type Inequality on Simplicial Complexes
CoRR
Sayan Mukherjee, Caroline J. Klivans, John Steenbergen
2012 A* conf
Local homology transfer and stratification learning.
SODA
Paul Bendich, Bei Wang, Sayan Mukherjee
2011 J jnl
Estimating variable structure and dependence in multitask learning via gradients.
Mach. Learn.
Justin Guinney, Qiang Wu, Sayan Mukherjee
2010 J jnl
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence.
J. Mach. Learn. Res.
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mukherjee
2010 J jnl
On the reproducibility of results of pathway analysis in genome-wide expression studies of colorectal cancers.
J. Biomed. Informatics
Rosalia Maglietta, Angela Distaso, Ada Piepoli, Orazio Palumbo, Massimo Carella, Annarita D'Addabbo, Sayan Mukherjee, Nicola Ancona
2010 — conf
Stratification Learning through Homology Inference.
AAAI Fall Symposium: Manifold Learning and Its Applications
Paul Bendich, Sayan Mukherjee, Bei Wang
2010 A conf
Supervised Dimension Reduction Using Bayesian Mixture Modeling.
AISTATS
Kai Mao, Feng Liang, Sayan Mukherjee
2009 J jnl
Comparative study of gene set enrichment methods.
BMC Bioinform.
Luca Abatangelo, Rosalia Maglietta, Angela Distaso, Annarita D'Addabbo, Teresa Maria Creanza, Sayan Mukherjee, Nicola Ancona
2008 — conf
Localized Sliced Inverse Regression.
NIPS
Qiang Wu, Sayan Mukherjee, Feng Liang
2008 J jnl
Modeling Cancer Progression via Pathway Dependencies.
PLoS Comput. Biol.
Elena J. Edelman, Justin Guinney, Jen-Tsan A. Chi, Phillip G. Febbo, Sayan Mukherjee
2008 — conf
Statistical Assessment of MSigDB Gene Sets in Colon Cancer.
KES (2)
Angela Distaso, Luca Abatangelo, Rosalia Maglietta, Teresa Maria Creanza, Ada Piepoli, Massimo Carella, Annarita D'Addabbo, Sayan Mukherjee, Nicola Ancona
2007 J jnl
Characterizing the Function Space for Bayesian Kernel Models.
J. Mach. Learn. Res.
Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert
2007 C conf
Decision Fusion of Circulating Markers for Breast Cancer Detection in Premenopausal Women.
BIBE
Jonathan L. Jesneck, Sayan Mukherjee, Loren W. Nolte, Anna E. Lokshin, Jeffrey R. Marks, Joseph Y. Lo
2007 J jnl
Genomic sweeping for hypermethylated genes.
Bioinform.
Liang Goh, Susan K. Murphy, Sayan Mukherjee, Terrence S. Furey
2006 — conf
Analysis of sample set enrichment scores: assaying the enrichment of sets of genes for individual samples in genome-wide expression profiles.
ISMB (Supplement of Bioinformatics)
Elena J. Edelman, Alessandro Porrello, Justin Guinney, Bala Balakumaran, Andrea Bild, Phillip G. Febbo, Sayan Mukherjee
2006 J jnl
Estimation of Gradients and Coordinate Covariation in Classification.
J. Mach. Learn. Res.
Sayan Mukherjee, Qiang Wu
2006 J jnl
Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation.
PLoS Comput. Biol.
Zhong Wang, Huntington F. Willard, Sayan Mukherjee, Terrence S. Furey
2006 J jnl
Learning Coordinate Covariances via Gradients.
J. Mach. Learn. Res.
Sayan Mukherjee, Ding-Xuan Zhou
2006 J jnl
Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization.
Adv. Comput. Math.
Sayan Mukherjee, Partha Niyogi, Tomaso A. Poggio, Ryan M. Rifkin
2005 — conf
Gene Selection via a Spectral Approach.
CVPR Workshops
Lior Wolf, Amnon Shashua, Sayan Mukherjee
2005 A* conf
Permutation Tests for Classification.
COLT
Polina Golland, Feng Liang, Sayan Mukherjee, Dmitry Panchenko
2003 J jnl
An Analytical Method for Multiclass Molecular Cancer Classification.
SIAM Rev.
Ryan M. Rifkin, Sayan Mukherjee, Pablo Tamayo, Sridhar Ramaswamy, Chen-Hsiang Yeang, Michael Angelo, Michael Reich, Tomaso A. Poggio, Eric S. Lander, Todd R. Golub, Jill P. Mesirov
2003 J jnl
Estimating Dataset Size Requirements for Classifying DNA Microarray Data.
J. Comput. Biol.
Sayan Mukherjee, Pablo Tamayo, Simon Rogers, Ryan M. Rifkin, Anna Engle, Colin Campbell, Todd R. Golub, Jill P. Mesirov
2002 J jnl
Choosing Multiple Parameters for Support Vector Machines.
Mach. Learn.
Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee
2002 — conf
Predicting Signal Peptides with Support Vector Machines.
SVM
Neelanjan Mukherjee, Sayan Mukherjee
2001 — conf
Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images.
CVPR (2)
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Tomaso A. Poggio
2001 — conf
Molecular classification of multiple tumor types.
ISMB (Supplement of Bioinformatics)
Chen-Hsiang Yeang, Sridhar Ramaswamy, Pablo Tamayo, Sayan Mukherjee, Ryan M. Rifkin, Michael Angelo, Michael Reich, Eric S. Lander, Jill P. Mesirov, Todd R. Golub
2000 — conf
Feature Selection for SVMs.
NIPS
Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso A. Poggio, Vladimir Vapnik