Saved in:
| Main Authors: | Vinod, Ashwin, Bajaj, Chandrajit |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.04079 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Motion Code: Robust Time Series Classification and Forecasting via Sparse Variational Multi-Stochastic Processes Learning
by: Bajaj, Chandrajit, et al.
Published: (2024)
by: Bajaj, Chandrajit, et al.
Published: (2024)
Self-Balancing, Memory Efficient, Dynamic Metric Space Data Maintenance, for Rapid Multi-Kernel Estimation
by: Ellendula, Aditya S, et al.
Published: (2025)
by: Ellendula, Aditya S, et al.
Published: (2025)
When Descent Is Too Stable: Event-Triggered Hamiltonian Learning to Optimize
by: Wang, Yi, et al.
Published: (2026)
by: Wang, Yi, et al.
Published: (2026)
Sample Efficient Learning of Factored Embeddings of Tensor Fields
by: Heo, Taemin, et al.
Published: (2022)
by: Heo, Taemin, et al.
Published: (2022)
A Differential and Pointwise Control Approach to Reinforcement Learning
by: Nguyen, Minh, et al.
Published: (2024)
by: Nguyen, Minh, et al.
Published: (2024)
Low-cost Robust Night-time Aerial Material Segmentation through Hyperspectral Data and Sparse Spatio-Temporal Learning
by: Bajaj, Chandrajit, et al.
Published: (2024)
by: Bajaj, Chandrajit, et al.
Published: (2024)
PHAST: Port-Hamiltonian Architecture for Structured Temporal Dynamics Forecasting
by: Bhardwaj, Shubham, et al.
Published: (2026)
by: Bhardwaj, Shubham, et al.
Published: (2026)
Learning Material-Aware Hamiltonian Risk Fields for Safe Navigation
by: Ellendula, Aditya Sai, et al.
Published: (2026)
by: Ellendula, Aditya Sai, et al.
Published: (2026)
GRL-SNAM: Geometric Reinforcement Learning with Path Differential Hamiltonians for Simultaneous Navigation and Mapping in Unknown Environments
by: Ellendula, Aditya Sai, et al.
Published: (2025)
by: Ellendula, Aditya Sai, et al.
Published: (2025)
Queryable LoRA: Instruction-Regularized Routing Over Shared Low-Rank Update Atoms
by: Vaidya, Omatharv Bharat, et al.
Published: (2026)
by: Vaidya, Omatharv Bharat, et al.
Published: (2026)
Reinforcement Learning for Molecular Dynamics Optimization: A Stochastic Pontryagin Maximum Principle Approach
by: Bajaj, Chandrajit, et al.
Published: (2022)
by: Bajaj, Chandrajit, et al.
Published: (2022)
Learning Sparse Codes with Entropy-Based ELBOs
by: Velychko, Dmytro, et al.
Published: (2023)
by: Velychko, Dmytro, et al.
Published: (2023)
Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data
by: McLennan, Luke, et al.
Published: (2025)
by: McLennan, Luke, et al.
Published: (2025)
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
by: Blessing, Denis, et al.
Published: (2024)
by: Blessing, Denis, et al.
Published: (2024)
Harnessing Data from Clustered LQR Systems: Personalized and Collaborative Policy Optimization
by: Kanakeri, Vinay, et al.
Published: (2025)
by: Kanakeri, Vinay, et al.
Published: (2025)
Generative Models with ELBOs Converging to Entropy Sums
by: Warnken, Jan, et al.
Published: (2024)
by: Warnken, Jan, et al.
Published: (2024)
Physics-informed neural networks via stochastic Hamiltonian dynamics learning
by: Bajaj, Chandrajit, et al.
Published: (2021)
by: Bajaj, Chandrajit, et al.
Published: (2021)
Adaptive, Robust and Scalable Bayesian Filtering for Online Learning
by: Duran-Martin, Gerardo
Published: (2025)
by: Duran-Martin, Gerardo
Published: (2025)
Towards Robust and Scalable Density-based Clustering via Graph Propagation
by: Zheng, Yingtao, et al.
Published: (2026)
by: Zheng, Yingtao, et al.
Published: (2026)
CoHiRF: Hierarchical Consensus for Interpretable Clustering Beyond Scalability Limits
by: Meziani, Katia, et al.
Published: (2025)
by: Meziani, Katia, et al.
Published: (2025)
Choosing the Right Regularizer for Applied ML: Simulation Benchmarks of Popular Scikit-learn Regularization Frameworks
by: Knight, Benjamin S., et al.
Published: (2026)
by: Knight, Benjamin S., et al.
Published: (2026)
Fast, Scalable, Energy-Efficient Non-element-wise Matrix Multiplication on FPGA
by: Zhu, Xuqi, et al.
Published: (2024)
by: Zhu, Xuqi, et al.
Published: (2024)
qPOTS: Efficient batch multiobjective Bayesian optimization via Pareto optimal Thompson sampling
by: Renganathan, Ashwin, et al.
Published: (2023)
by: Renganathan, Ashwin, et al.
Published: (2023)
Scalable Bayesian Learning with posteriors
by: Duffield, Samuel, et al.
Published: (2024)
by: Duffield, Samuel, et al.
Published: (2024)
A Bayesian Approach to Clustering via the Proper Bayesian Bootstrap: the Bayesian Bagged Clustering (BBC) algorithm
by: Quetti, Federico Maria, et al.
Published: (2024)
by: Quetti, Federico Maria, et al.
Published: (2024)
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes
by: Chauhan, Vinod Kumar, et al.
Published: (2025)
by: Chauhan, Vinod Kumar, et al.
Published: (2025)
Bayesian Supervised Causal Clustering
by: Wang, Luwei, et al.
Published: (2026)
by: Wang, Luwei, et al.
Published: (2026)
Analysis, Identification and Prediction of Parkinson Disease Sub-Types and Progression through Machine Learning
by: Ram, Ashwin
Published: (2023)
by: Ram, Ashwin
Published: (2023)
Towards Scalable Bayesian Optimization via Gradient-Informed Bayesian Neural Networks
by: Makrygiorgos, Georgios, et al.
Published: (2025)
by: Makrygiorgos, Georgios, et al.
Published: (2025)
Co-Learning Bayesian Optimization
by: Guo, Zhendong, et al.
Published: (2025)
by: Guo, Zhendong, et al.
Published: (2025)
Scalable Monte Carlo for Bayesian Learning
by: Fearnhead, Paul, et al.
Published: (2024)
by: Fearnhead, Paul, et al.
Published: (2024)
Enhancing Kernel Power K-means: Scalable and Robust Clustering with Random Fourier Features and Possibilistic Method
by: Chen, Yixi, et al.
Published: (2025)
by: Chen, Yixi, et al.
Published: (2025)
Robust Federated Personalised Mean Estimation for the Gaussian Mixture Model
by: Managoli, Malhar A., et al.
Published: (2025)
by: Managoli, Malhar A., et al.
Published: (2025)
Scalable Varied-Density Clustering via Graph Propagation
by: Pham, Ninh, et al.
Published: (2025)
by: Pham, Ninh, et al.
Published: (2025)
A Scalable Global Optimization Algorithm For Constrained Clustering
by: Chumpitaz-Flores, Pedro, et al.
Published: (2025)
by: Chumpitaz-Flores, Pedro, et al.
Published: (2025)
Scalable and Adaptive Spectral Embedding for Attributed Graph Clustering
by: Liu, Yunhui, et al.
Published: (2024)
by: Liu, Yunhui, et al.
Published: (2024)
Robust and Scalable Variational Bayes
by: Padilla, Carlos Misael Madrid, et al.
Published: (2025)
by: Padilla, Carlos Misael Madrid, et al.
Published: (2025)
Summaries as Centroids for Interpretable and Scalable Text Clustering
by: Diaz-Rodriguez, Jairo
Published: (2025)
by: Diaz-Rodriguez, Jairo
Published: (2025)
Scalable Bayesian Inference for Nonlinear Conservation Laws
by: Weiland, Tim, et al.
Published: (2026)
by: Weiland, Tim, et al.
Published: (2026)
Transformers can do Bayesian Clustering
by: Bhaskaran, Prajit, et al.
Published: (2025)
by: Bhaskaran, Prajit, et al.
Published: (2025)
Similar Items
-
Motion Code: Robust Time Series Classification and Forecasting via Sparse Variational Multi-Stochastic Processes Learning
by: Bajaj, Chandrajit, et al.
Published: (2024) -
Self-Balancing, Memory Efficient, Dynamic Metric Space Data Maintenance, for Rapid Multi-Kernel Estimation
by: Ellendula, Aditya S, et al.
Published: (2025) -
When Descent Is Too Stable: Event-Triggered Hamiltonian Learning to Optimize
by: Wang, Yi, et al.
Published: (2026) -
Sample Efficient Learning of Factored Embeddings of Tensor Fields
by: Heo, Taemin, et al.
Published: (2022) -
A Differential and Pointwise Control Approach to Reinforcement Learning
by: Nguyen, Minh, et al.
Published: (2024)