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Attentive Neural Processes

17 January 2019

Hyunjik Kim

A. Mnih

Jonathan Richard Schwarz

Papers citing "Attentive Neural Processes"

50 / 273 papers shown

Title
Generative Models as Distributions of Functions Emilien Dupont Yee Whye Teh Arnaud Doucet 95 109 0 09 Feb 2021
Meta-Learning for Koopman Spectral Analysis with Short Time-series Tomoharu Iwata Yoshinobu Kawahara AI4TS 57 0 0 09 Feb 2021
Functional optimal transport: map estimation and domain adaptation for functional data Jiacheng Zhu Aritra Guha Dat Do Mengdi Xu X. Nguyen Ding Zhao OT 104 8 0 07 Feb 2021
NRTSI: Non-Recurrent Time Series Imputation Siyuan Shan Yang Li Junier B. Oliva AI4TS 89 37 0 05 Feb 2021
Unsupervised clustering of series using dynamic programming Karthigan Sinnathamby Chang-Yu Hou Lalitha Venkataramanan V. Gkortsas Franccois Fleuret 30 0 0 23 Jan 2021
Convolutional conditional neural processes for local climate downscaling Anna Vaughan Will Tebbutt J. S. Hosking Richard Turner BDL 89 49 0 20 Jan 2021
The Gaussian Neural Process W. Bruinsma James Requeima Andrew Y. K. Foong Jonathan Gordon Richard Turner BDL 77 29 0 10 Jan 2021
Context-Aware Safe Reinforcement Learning for Non-Stationary Environments Baiming Chen Zuxin Liu Jiacheng Zhu Mengdi Xu Wenhao Ding Ding Zhao 64 38 0 02 Jan 2021
Multi-Instance Aware Localization for End-to-End Imitation Learning S. Gubbi Raviteja Upadrashta Shishir Kolathaya B. Amrutur 39 1 0 26 Dec 2020
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? Antoine Grosnit Alexander I. Cowen-Rivers Rasul Tutunov Ryan-Rhys Griffiths Jun Wang Haitham Bou-Ammar 105 14 0 15 Dec 2020
NP-ODE: Neural Process Aided Ordinary Differential Equations for Uncertainty Quantification of Finite Element Analysis Yinan Wang Kaiwen Wang W. Cai Xiaowei Yue 71 4 0 12 Dec 2020
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes P. Holderrieth M. Hutchinson Yee Whye Teh BDL 110 30 0 25 Nov 2020
A Worrying Analysis of Probabilistic Time-series Models for Sales Forecasting Seungjae Jung KyungHyun Kim Hanock Kwak Young-Jin Park AI4TS 34 6 0 21 Nov 2020
Factorized Neural Processes for Neural Processes: $K$ -Shot Prediction of Neural Responses R. J. Cotton Fabian H. Sinz A. Tolias 53 7 0 22 Oct 2020
Function Contrastive Learning of Transferable Meta-Representations Muhammad Waleed Gondal S. Joshi Nasim Rahaman Stefan Bauer Manuel Wüthrich Bernhard Schölkopf SSL 52 19 0 14 Oct 2020
Meta-Active Learning for Node Response Prediction in Graphs Tomoharu Iwata 25 0 0 12 Oct 2020
Few-shot Learning for Spatial Regression Tomoharu Iwata Yusuke Tanaka 98 11 0 09 Oct 2020
Uncertainty in Neural Processes Saeid Naderiparizi Ke-Li Chiu Benjamin Bloem-Reddy Frank Wood UQCV BDL AI4CE 63 5 0 08 Oct 2020
Gaussian Process Molecule Property Prediction with FlowMO Henry B. Moss Ryan-Rhys Griffiths 123 23 0 02 Oct 2020
Few-shot Learning for Time-series Forecasting Tomoharu Iwata Atsutoshi Kumagai AI4TS 51 18 0 30 Sep 2020
Message Passing Neural Processes Ben Day Cătălina Cangea Arian R. Jamasb Pietro Lio 75 12 0 29 Sep 2020
Improving Query Efficiency of Black-box Adversarial Attack Yang Bai Yuyuan Zeng Yong Jiang Yisen Wang Shutao Xia Weiwei Guo AAML MLAU 122 53 0 24 Sep 2020
Meta-Learning with Shared Amortized Variational Inference E. Iakovleva Jakob Verbeek Alahari Karteek OOD FedML BDL 55 22 0 27 Aug 2020
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables Q. Wang H. V. Hoof BDL 68 42 0 21 Aug 2020
Learning from Irregularly-Sampled Time Series: A Missing Data Perspective Steven Cheng-Xian Li Benjamin M. Marlin AI4TS 55 56 0 17 Aug 2020
Bootstrapping Neural Processes Juho Lee Yoonho Lee Jungtaek Kim Eunho Yang Sung Ju Hwang Yee Whye Teh UQCV BDL 87 43 0 07 Aug 2020
Graph-Based Continual Learning Binh Tang David S. Matteson BDL CLL 76 37 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 Turner BDL 93 78 0 02 Jul 2020
Robustifying Sequential Neural Processes Jaesik Yoon Gautam Singh Sungjin Ahn 69 27 0 29 Jun 2020
Set Based Stochastic Subsampling Bruno Andreis Seanie Lee A. Nguyen Juho Lee Eunho Yang Sung Ju Hwang BDL 44 0 0 25 Jun 2020
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes Mengdi Xu Wenhao Ding Jiacheng Zhu Zuxin Liu Baiming Chen Ding Zhao CLL OffRL 100 35 0 19 Jun 2020
MetaSDF: Meta-learning Signed Distance Functions Vincent Sitzmann E. R. Chan Richard Tucker Noah Snavely Gordon Wetzstein 69 251 0 17 Jun 2020
Implicit Neural Representations with Periodic Activation Functions Vincent Sitzmann Julien N. P. Martel Alexander W. Bergman David B. Lindell Gordon Wetzstein AI4TS 242 2,585 0 17 Jun 2020
NP-PROV: Neural Processes with Position-Relevant-Only Variances Xuesong Wang Lina Yao Xianzhi Wang Feiping Nie BDL 66 3 0 15 Jun 2020
Task-similarity Aware Meta-learning through Nonparametric Kernel Regression Arun Venkitaraman Anders Hansson B. Wahlberg 84 8 0 12 Jun 2020
Learning to Learn Kernels with Variational Random Features Xiantong Zhen Hao Sun Yingjun Du Jun Xu Yilong Yin Ling Shao Cees G. M. Snoek DRL 72 34 0 11 Jun 2020
Neural Physicist: Learning Physical Dynamics from Image Sequences Baocheng Zhu Shijun Wang James Y. Zhang AI4CE 31 1 0 09 Jun 2020
Meta Learning as Bayes Risk Minimization S. Maeda Toshiki Nakanishi Masanori Koyama BDL 28 1 0 02 Jun 2020
From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic Risto Miikkulainen Olivier Francon Elliot Meyerson Xin Qiu Elisa Canzani Babak Hodjat 64 3 0 28 May 2020
Kernel Self-Attention in Deep Multiple Instance Learning Dawid Rymarczyk Adriana Borowa Jacek Tabor Bartosz Zieliñski SSL 125 6 0 25 May 2020
Differentiable Mapping Networks: Learning Structured Map Representations for Sparse Visual Localization Peter Karkus A. Angelova Vincent Vanhoucke Rico Jonschkowski 70 11 0 19 May 2020
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients S. Hu Pablo G. Moreno Yanghua Xiao Xin Shen G. Obozinski Neil D. Lawrence Andreas C. Damianou BDL 94 125 0 27 Apr 2020
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context Wenyu Zhang Skyler Seto Devesh K. Jha 71 5 0 26 Mar 2020
Energy-Based Processes for Exchangeable Data Mengjiao Yang Bo Dai H. Dai Dale Schuurmans 83 12 0 17 Mar 2020
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows Ruizhi Deng B. Chang Marcus A. Brubaker Greg Mori Andreas M. Lehrmann 104 52 0 24 Feb 2020
Deep Fourier Kernel for Self-Attentive Point Processes Shixiang Zhu Minghe Zhang Ruyi Ding Yao Xie 3DPC 45 3 0 17 Feb 2020
$π$ VAE: a stochastic process prior for Bayesian deep learning with MCMC Swapnil Mishra Seth Flaxman Tresnia Berah Harrison Zhu Mikko S. Pakkanen Samir Bhatt BDL 31 3 0 17 Feb 2020
Local Nonparametric Meta-Learning Wonjoon Goo S. Niekum 85 3 0 09 Feb 2020
Model Inversion Networks for Model-Based Optimization Aviral Kumar Sergey Levine OffRL 97 100 0 31 Dec 2019
MetaFun: Meta-Learning with Iterative Functional Updates Jin Xu Jean-François Ton Hyunjik Kim Adam R. Kosiorek Yee Whye Teh 78 68 0 05 Dec 2019