The Functional Neural Process

19 June 2019

Papers citing "The Functional Neural Process"

50 / 58 papers shown

Title
Dimension Agnostic Neural Processes Hyungi Lee Chaeyun Jang Dongbok Lee Juho Lee UQCV AI4CE 52 0 0 28 Feb 2025
Bridge the Inference Gaps of Neural Processes via Expectation Maximization Q. Wang Marco Federici H. V. Hoof UQCV BDL 39 13 0 08 Jan 2025
Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity Harshavardhan Kamarthi Aditya B. Sasanur Xinjie Tong Xingyu Zhou James Peters Joe Czyzyk B. Aditya Prakash AI4TS 26 2 0 02 Jul 2024
Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting Harshavardhan Kamarthi Lingkai Kong Alexander Rodríguez Chao Zhang B Aditya Prakash AI4TS 43 0 0 02 Jul 2024
Spectral Convolutional Conditional Neural Processes Peiman Mohseni Nick Duffield 37 3 0 19 Apr 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 32 2 0 29 Feb 2024
PEMS: Pre-trained Epidemic Time-series Models Harshavardhan Kamarthi B. A. Prakash AI4TS 26 2 0 14 Nov 2023
Latent Task-Specific Graph Network Simulators Philipp Dahlinger Niklas Freymuth Michael Volpp Tai Hoang Gerhard Neumann AI4CE 27 0 0 09 Nov 2023
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting Harshavardhan Kamarthi Lingkai Kong Alexander Rodríguez Chao Zhang B. Prakash AI4TS 30 5 0 17 Oct 2023
Machine Learning for Infectious Disease Risk Prediction: A Survey Mutong Liu Yang Liu Jiming Liu LM&MA AI4CE 18 0 0 06 Aug 2023
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation Jianfeng Wang Daniela Massiceti Xiaolin Hu Vladimir Pavlovic Thomas Lukasiewicz UQCV 30 3 0 05 Aug 2023
Geometric Neural Diffusion Processes Emile Mathieu Vincent Dutordoir M. Hutchinson Valentin De Bortoli Yee Whye Teh Richard E. Turner DiffM 36 8 0 11 Jul 2023
Disentangled Multi-Fidelity Deep Bayesian Active Learning D. Wu Ruijia Niu Matteo Chinazzi Yi-An Ma Rose Yu AI4CE 30 7 0 07 May 2023
Martingale Posterior Neural Processes Hyungi Lee Eunggu Yun G. Nam Edwin Fong Juho Lee UQCV 25 7 0 19 Apr 2023
NP-Match: Towards a New Probabilistic Model for Semi-Supervised Learning Jianfeng Wang Xiaolin Hu Thomas Lukasiewicz AAML BDL 28 0 0 31 Jan 2023
Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior Yohan Jung Jinkyoo Park BDL 16 0 0 22 Oct 2022
Spectral Diffusion Processes Angus Phillips Thomas Seror M. Hutchinson Valentin De Bortoli Arnaud Doucet Emile Mathieu DiffM 59 15 0 28 Sep 2022
Compositional Law Parsing with Latent Random Functions Fan Shi Bin Li Xiangyang Xue CoGe 21 4 0 15 Sep 2022
The Neural Process Family: Survey, Applications and Perspectives Saurav Jha Dong Gong Xuesong Wang Richard E. Turner L. Yao BDL 73 24 0 01 Sep 2022
Data-Centric Epidemic Forecasting: A Survey Alexander Rodríguez Harshavardhan Kamarthi Pulak Agarwal Javen Ho Mira Patel Suchet Sapre B. Prakash OOD 29 18 0 19 Jul 2022
NP-Match: When Neural Processes meet Semi-Supervised Learning Jianfeng Wang Thomas Lukasiewicz Daniela Massiceti Xiaolin Hu Vladimir Pavlovic A. Neophytou BDL 63 41 0 03 Jul 2022
Category-Agnostic 6D Pose Estimation with Conditional Neural Processes Yumeng Li Ni Gao Hanna Ziesche Gerhard Neumann 26 5 0 14 Jun 2022
Multi-fidelity Hierarchical Neural Processes D. Wu Matteo Chinazzi Alessandro Vespignani Yi-An Ma Rose Yu AI4CE 10 13 0 10 Jun 2022
Meta-Learning Regrasping Strategies for Physical-Agnostic Objects Ni Gao Jingyu Zhang Ruijie Chen Ngo Anh Vien Hanna Ziesche Gerhard Neumann 38 10 0 23 May 2022
What Matters For Meta-Learning Vision Regression Tasks? Ni Gao Hanna Ziesche Ngo Anh Vien Michael Volpp Gerhard Neumann VLM 18 29 0 09 Mar 2022
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning Raed Al Kontar Naichen Shi Xubo Yue Seokhyun Chung E. Byon ... C. Okwudire Garvesh Raskutti R. Saigal Karandeep Singh Ye Zhisheng FedML 36 50 0 09 Nov 2021
ST-MAML: A Stochastic-Task based Method for Task-Heterogeneous Meta-Learning Zhe Wang J. E. Grigsby Arshdeep Sekhon Yanjun Qi 50 4 0 27 Sep 2021
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting Harshavardhan Kamarthi Lingkai Kong Alexander Rodríguez Chao Zhang B. Prakash AI4TS 46 17 0 15 Sep 2021
Meta-learning Amidst Heterogeneity and Ambiguity Kyeongryeol Go Seyoung Yun 24 1 0 05 Jul 2021
Relational VAE: A Continuous Latent Variable Model for Graph Structured Data Charilaos Mylonas I. Abdallah Eleni Chatzi BDL 13 1 0 30 Jun 2021
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data Jens Petersen Gregor Koehler David Zimmerer Fabian Isensee Paul F. Jäger Klaus H. Maier-Hein BDL AI4TS 31 3 0 09 Jun 2021
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting Harshavardhan Kamarthi Lingkai Kong Alexander Rodríguez Chao Zhang B. Prakash AI4TS BDL 23 20 0 07 Jun 2021
Deep Bayesian Active Learning for Accelerating Stochastic Simulation D. Wu Ruijia Niu Matteo Chinazzi Alessandro Vespignani Yi-An Ma Rose Yu AI4CE 30 8 0 05 Jun 2021
Evidential Turing Processes M. Kandemir Abdullah Akgul Manuel Haussmann Gözde B. Ünal EDL UQCV BDL 33 9 0 02 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 29 124 0 14 May 2021
Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding Bruno Andreis Jeffrey Willette Juho Lee Sung Ju Hwang 22 9 0 02 Mar 2021
Group Equivariant Conditional Neural Processes M. Kawano Wataru Kumagai Akiyoshi Sannai Yusuke Iwasawa Y. Matsuo BDL 45 20 0 17 Feb 2021
Autoencoding Variational Autoencoder A. Cemgil Sumedh Ghaisas Krishnamurthy Dvijotham Sven Gowal Pushmeet Kohli DRL BDL 23 41 0 07 Dec 2020
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch BDL UQCV 19 22 0 04 Dec 2020
Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang Bin Dai David Wipf Jun Zhu 14 39 0 25 Oct 2020
Incorporating Interpretable Output Constraints in Bayesian Neural Networks Wanqian Yang Lars Lorch Moritz Graule Himabindu Lakkaraju Finale Doshi-Velez UQCV BDL 17 16 0 21 Oct 2020
Message Passing Neural Processes Ben Day Cătălina Cangea Arian R. Jamasb Pietro Lió 24 11 0 29 Sep 2020
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables Q. Wang H. V. Hoof BDL 21 42 0 21 Aug 2020
Bootstrapping Neural Processes Juho Lee Yoonho Lee Jungtaek Kim Eunho Yang Sung Ju Hwang Yee Whye Teh UQCV BDL 18 42 0 07 Aug 2020
Graph-Based Continual Learning Binh Tang David S. Matteson BDL CLL 29 36 0 09 Jul 2020
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes Andrew Y. K. Foong W. Bruinsma Jonathan Gordon Yann Dubois James Requeima Richard E. Turner BDL 11 77 0 02 Jul 2020
Robustifying Sequential Neural Processes Jaesik Yoon Gautam Singh Sungjin Ahn 26 27 0 29 Jun 2020
Calibrated Adversarial Refinement for Stochastic Semantic Segmentation Elias Kassapis G. Dikov D. K. Gupta C. Nugteren 38 17 0 23 Jun 2020
Predictive Complexity Priors Eric T. Nalisnick Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV 29 19 0 18 Jun 2020
NP-PROV: Neural Processes with Position-Relevant-Only Variances Xuesong Wang Lina Yao Xianzhi Wang Feiping Nie BDL 24 3 0 15 Jun 2020