Deep Kernel Learning

6 November 2015

Papers citing "Deep Kernel Learning"

50 / 504 papers shown

Title
Bayesian Active Learning for Semantic Segmentation Sima Didari Wenjun Hu Jae Oh Woo Heng Hao Hankyu Moon Seungjai Min 125 1 0 03 Aug 2024
DKL-KAN: Scalable Deep Kernel Learning using Kolmogorov-Arnold Networks Shrenik Zinage Sudeepta Mondal S. Sarkar 107 7 0 30 Jul 2024
Bayesian meta learning for trustworthy uncertainty quantification Zhenyuan Yuan Thinh T. Doan UQCV 87 0 0 27 Jul 2024
Online Drift Detection with Maximum Concept Discrepancy Ke Wan Yi Liang Susik Yoon 107 3 0 07 Jul 2024
Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent Mohit Kumar Alexander Valentinitsch Magdalena Fuchs Mathias Brucker Juliana Bowles Adnan Husaković Ali Abbas Bernhard A. Moser 109 0 0 05 Jul 2024
Improving Hyperparameter Optimization with Checkpointed Model Weights Nikhil Mehta Jonathan Lorraine Steve Masson Ramanathan Arunachalam Zaid Pervaiz Bhat James Lucas Arun George Zachariah 107 4 0 26 Jun 2024
OCCAM: Online Continuous Controller Adaptation with Meta-Learned Models Hersh Sanghvi Spencer Folk Camillo J Taylor 94 3 0 25 Jun 2024
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise T. Pouplin Alan Jeffares Nabeel Seedat Mihaela van der Schaar 468 3 0 05 Jun 2024
Stein Random Feature Regression Houston Warren Rafael Oliveira Fabio Ramos BDL 102 0 0 01 Jun 2024
Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach Mohammed Amine Gharsallaoui Bhupinderjeet Singh Supriya Savalkar Aryan Deshwal Yan Yan Ananth Kalyanaraman Kirti Rajagopalan J. Doppa AI4CE 65 1 0 31 May 2024
Recurrent Deep Kernel Learning of Dynamical Systems N. Botteghi Paolo Motta Andrea Manzoni P. Zunino Mengwu Guo 55 1 0 30 May 2024
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation Dong Bok Lee Aoxuan Silvia Zhang Byung-Hoon Kim Junhyeon Park Juho Lee Sung Ju Hwang Haebeom Lee 108 2 0 28 May 2024
Infinite-Dimensional Feature Interaction Chenhui Xu Fuxun Yu Maoliang Li Zihao Zheng Zirui Xu Jinjun Xiong Xiang Chen 98 1 0 22 May 2024
Efficient modeling of sub-kilometer surface wind with Gaussian processes and neural networks Francesco Zanetta D. Nerini Matteo Buzzi Henry Moss 63 0 0 21 May 2024
Integration of Scanning Probe Microscope with High-Performance Computing: fixed-policy and reward-driven workflows implementation Yu Liu Utkarsh Pratiush Jason Bemis R. Proksch Reece Emery ... Yu-Chen Liu Jan-Chi Yang Stanislav Udovenko Susan E. Trolier-McKinstry Sergei V. Kalinin 26 6 0 20 May 2024
Active Learning with Fully Bayesian Neural Networks for Discontinuous and Nonstationary Data Maxim Ziatdinov AI4CE 73 4 0 16 May 2024
Spectral complexity of deep neural networks Simmaco Di Lillo Domenico Marinucci Michele Salvi Stefano Vigogna BDL 171 2 0 15 May 2024
No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes Minbiao Han Fengxue Zhang Yuxin Chen 68 4 0 14 May 2024
The Role of Predictive Uncertainty and Diversity in Embodied AI and Robot Learning Ransalu Senanayake 96 9 0 06 May 2024
Accelerating Convergence in Bayesian Few-Shot Classification Tianjun Ke Haoqun Cao Feng Zhou 101 0 0 02 May 2024
Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning B. Slautin Yongtao Liu Hiroshi Funakubo Rama K Vasudevan M. Ziatdinov Sergei V. Kalinin 56 7 0 19 Apr 2024
Variational Bayesian Last Layers James Harrison John Willes Jasper Snoek BDL UQCV 146 34 0 17 Apr 2024
Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite Data Nils Lehmann N. Gottschling Stefan Depeweg Eric T. Nalisnick 86 1 0 12 Apr 2024
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification Yibo Miao Yu Lei Feng Zhou Zhijie Deng VLM UQCV BDL 101 3 0 30 Mar 2024
Workload Estimation for Unknown Tasks: A Survey of Machine Learning Under Distribution Shift Josh Bhagat Smith Julie A. Adams 101 0 0 20 Mar 2024
Multi-Fidelity Reinforcement Learning for Time-Optimal Quadrotor Re-planning Gilhyun Ryou Geoffrey Wang S. Karaman 106 3 0 13 Mar 2024
Explainable Learning with Gaussian Processes Kurt Butler Guanchao Feng Petar M. Djurić 123 2 0 11 Mar 2024
A prediction rigidity formalism for low-cost uncertainties in trained neural networks Filippo Bigi Sanggyu Chong Michele Ceriotti Federico Grasselli 75 6 0 04 Mar 2024
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling Ruijia Niu D. Wu Kai Kim Yi-An Ma D. Watson‐Parris Rose Yu AI4CE 85 4 0 29 Feb 2024
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints Lingkai Kong Yuanqi Du Wenhao Mu Kirill Neklyudov Valentin De Bortol ... D. Wu Aaron Ferber Yi-An Ma Carla P. Gomes Chao Zhang 82 13 0 28 Feb 2024
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling Peter Eckmann D. Wu G. Heinzelmann Michael K. Gilson Rose Yu AI4CE 74 4 0 16 Feb 2024
Attention as Robust Representation for Time Series Forecasting Peisong Niu Tian Zhou Xue Wang Liang Sun Rong Jin AI4TS 63 5 0 08 Feb 2024
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules? Agustinus Kristiadi Felix Strieth-Kalthoff Marta Skreta Pascal Poupart Alán Aspuru-Guzik Geoff Pleiss 87 23 0 07 Feb 2024
A General Theory for Kernel Packets: from state space model to compactly supported basis Liang Ding Rui Tuo 34 1 0 06 Feb 2024
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning Idan Achituve I. Diamant Arnon Netzer Gal Chechik Ethan Fetaya UQCV 92 7 0 06 Feb 2024
Large Language Models to Enhance Bayesian Optimization Tennison Liu Nicolás Astorga Nabeel Seedat M. Schaar 156 59 0 06 Feb 2024
Combining additivity and active subspaces for high-dimensional Gaussian process modeling M. Binois Victor Picheny 90 0 0 06 Feb 2024
Kernel PCA for Out-of-Distribution Detection Kun Fang Qinghua Tao Kexin Lv Mingzhen He Xiaolin Huang Jie Yang OODD 126 4 0 05 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 139 35 0 01 Feb 2024
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach Mahrokh Ghoddousi Boroujeni Andreas Krause Giancarlo Ferrari-Trecate FedML 129 3 0 16 Jan 2024
Hybrid Modeling Design Patterns Maja Rudolph Stefan Kurz Barbara Rakitsch AI4CE 87 9 0 29 Dec 2023
Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation Melrose Roderick Felix Berkenkamp Fatemeh Sheikholeslami Zico Kolter UQCV 34 0 0 29 Dec 2023
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs Kevin Course P. Nair 94 3 0 16 Dec 2023
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation Tomoharu Iwata Atsutoshi Kumagai BDL UQCV 76 1 0 13 Dec 2023
Variational Elliptical Processes Maria B˙ankestad Jens Sjölund Jalil Taghia Thomas B. Schon 75 2 0 21 Nov 2023
Deep Bayesian Reinforcement Learning for Spacecraft Proximity Maneuvers and Docking Desong Du Naiming Qi Yanfang Liu Wei Pan 64 0 0 07 Nov 2023
Joint Composite Latent Space Bayesian Optimization Natalie Maus Zhiyuan Jerry Lin Maximilian Balandat E. Bakshy BDL 99 2 0 03 Nov 2023
Advancing Bayesian Optimization via Learning Correlated Latent Space Seunghun Lee Jaewon Chu S. Kim Juyeon Ko Hyunwoo J. Kim BDL 134 8 0 31 Oct 2023
Clairvoyance: A Pipeline Toolkit for Medical Time Series Daniel Jarrett Jinsung Yoon Ioana Bica Zhaozhi Qian A. Ercole M. Schaar AI4TS 87 36 0 28 Oct 2023
Policy Gradient with Kernel Quadrature Satoshi Hayakawa Tetsuro Morimura OffRL BDL 99 1 0 23 Oct 2023