Shubhendu Trivedi

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 33

Top Topics

Top Venues

Publications

Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models. Trans. Mach. Learn. Res. 2024 (2024)
Mircea Petrache, Shubhendu Trivedi
Position Paper: Generalized grammar rules and structure-based generalization beyond classical equivariance for lexical tasks and transduction. CoRR (2024)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Contextualized Sequence Likelihood: Enhanced Confidence Scores for Natural Language Generation. CoRR (2024)
Mircea Petrache, Shubhendu Trivedi
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance. NeurIPS (2023)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks. ICLR (2023)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models. CoRR (2023)
Mircea Petrache, Shubhendu Trivedi
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance. CoRR (2023)
Zhen Lin, Shubhendu Trivedi, Cao Xiao, Jimeng Sun
Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control. CoRR (2023)
Zhen Lin, Shubhendu Trivedi, Cao Xiao, Jimeng Sun
Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control. ICML (2023)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Conformal Prediction with Temporal Quantile Adjustments. CoRR (2022)
Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? ICLR (2022)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Conformal Prediction with Temporal Quantile Adjustments. NeurIPS (2022)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Conformal Prediction Intervals with Temporal Dependence. CoRR (2022)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Conformal Prediction Intervals with Temporal Dependence. Trans. Mach. Learn. Res. 2022 (2022)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks. CoRR (2022)
Zhen Lin, Nicholas Huang, Camille Avestruz, W. L. Kimmy Wu, Shubhendu Trivedi, João Caldeira, Brian Nord
DeepSZ: Identification of Sunyaev-Zel'dovich Galaxy Clusters using Deep Learning. CoRR (2021)
Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? CoRR (2021)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Locally Valid and Discriminative Confidence Intervals for Deep Learning Models. CoRR (2021)
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Locally Valid and Discriminative Prediction Intervals for Deep Learning Models. NeurIPS (2021)
Shubhendu Trivedi, J. Wang
The Expected Jacobian Outerproduct: Theory and Empirics. CoRR (2020)
Suhas Lohit, Shubhendu Trivedi
Rotation-Invariant Autoencoders for Signals on Spheres. CoRR (2020)
James Amundson, James Annis, Camille Avestruz, D. Bowring, João Caldeira, Giuseppe Cerati, C. Chang, Scott Dodelson, D. Elvira, A. Farahi, K. Genser, Lindsey Gray, Oliver Gutsche, Philip C. Harris, Jamie Kinney, James B. Kowalkowski, Rob Kutschke, S. Mrenna, Brian Nord, A. Para, Kevin Pedro, Gabriel N. Perdue, A. Scheinker, Panagiotis Spentzouris, J. St. John, Nhan Tran, Shubhendu Trivedi, Laura Trouille, W. L. K. Wu, C. R. Bom
Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan". CoRR (2019)
João Caldeira, W. L. K. Wu, Brian Nord, Camille Avestruz, Shubhendu Trivedi, K. T. Story
DeepCMB: Lensing reconstruction of the cosmic microwave background with deep neural networks. Astron. Comput. 28 (2019)
Pramod Kaushik Mudrakarta, Shubhendu Trivedi, Risi Kondor
Asymmetric Multiresolution Matrix Factorization. CoRR (2019)
Kirk Swanson, Shubhendu Trivedi, Joshua Lequieu, Kyle Swanson, Risi Kondor
Deep Learning for Automated Classification and Characterization of Amorphous Materials. CoRR (2019)
Risi Kondor, Zhen Lin, Shubhendu Trivedi
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network. CoRR (2018)
Risi Kondor, Shubhendu Trivedi
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups. ICML (2018)
Risi Kondor, Zhen Lin, Shubhendu Trivedi
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network. NeurIPS (2018)
Risi Kondor, Shubhendu Trivedi
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups. CoRR (2018)
Risi Kondor, Hy Truong Son, Horace Pan, Brandon M. Anderson, Shubhendu Trivedi
Covariant Compositional Networks For Learning Graphs. CoRR (2018)
Risi Kondor, Hy Truong Son, Horace Pan, Brandon M. Anderson, Shubhendu Trivedi
Covariant Compositional Networks For Learning Graphs. ICLR (Workshop) (2018)
João Caldeira, W. L. K. Wu, Brian Nord, Camille Avestruz, Shubhendu Trivedi, K. T. Story
DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks. CoRR (2018)
Shubhendu Trivedi
Discriminative Learning of Similarity and Group Equivariant Representations. CoRR (2018)
Shubhendu Trivedi, Zachary A. Pardos, Neil T. Heffernan
The Utility of Clustering in Prediction Tasks. CoRR (2015)
Shubhendu Trivedi, Jialei Wang, Samory Kpotufe, Gregory Shakhnarovich
A Consistent Estimator of the Expected Gradient Outerproduct. UAI (2014)
Shubhendu Trivedi, David A. McAllester, Greg Shakhnarovich
Discriminative Metric Learning by Neighborhood Gerrymandering. NIPS (2014)
Fei Song, Shubhendu Trivedi, Yutao Wang, Gábor N. Sárközy, Neil T. Heffernan
Applying Clustering to the Problem of Predicting Retention within an ITS: Comparing Regularity Clustering with Traditional Methods. FLAIRS Conference (2013)
Zachary A. Pardos, Shubhendu Trivedi, Neil T. Heffernan, Gábor N. Sárközy
Clustered Knowledge Tracing. ITS (2012)
Zachary A. Pardos, Qing Yang Wang, Shubhendu Trivedi
The real world significance of performance prediction. EDM (2012)
Gábor N. Sárközy, Fei Song, Endre Szemerédi, Shubhendu Trivedi
A Practical Regularity Partitioning Algorithm and its Applications in Clustering CoRR (2012)
Shubhendu Trivedi, Zachary A. Pardos, Gábor N. Sárközy, Neil T. Heffernan
Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction. EDM (2012)
Shubhendu Trivedi, Zachary A. Pardos, Gábor N. Sárközy, Neil T. Heffernan
Spectral Clustering in Educational Data Mining. EDM (2011)
Shubhendu Trivedi, Zachary A. Pardos, Neil T. Heffernan
Clustering Students to Generate an Ensemble to Improve Standard Test Score Predictions. AIED (2011)