Attentive Neural Processes

17 January 2019

Hyunjik Kim

A. Mnih

Jonathan Richard Schwarz

Papers citing "Attentive Neural Processes"

50 / 266 papers shown

Title
Context-Aware Safe Reinforcement Learning for Non-Stationary Environments Baiming Chen Zuxin Liu Jiacheng Zhu Mengdi Xu Wenhao Ding Ding Zhao 25 35 0 02 Jan 2021
Multi-Instance Aware Localization for End-to-End Imitation Learning S. Gubbi Raviteja Upadrashta Shishir Kolathaya B. Amrutur 9 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 19 13 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 17 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 36 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 12 4 0 21 Nov 2020
Factorized Neural Processes for Neural Processes: $K$ -Shot Prediction of Neural Responses R. J. Cotton Fabian H. Sinz A. Tolias 6 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 15 19 0 14 Oct 2020
Meta-Active Learning for Node Response Prediction in Graphs Tomoharu Iwata 11 0 0 12 Oct 2020
Few-shot Learning for Spatial Regression Tomoharu Iwata Yusuke Tanaka 30 11 0 09 Oct 2020
Uncertainty in Neural Processes Saeid Naderiparizi Ke-Li Chiu Benjamin Bloem-Reddy Frank Wood UQCV BDL AI4CE 11 4 0 08 Oct 2020
Gaussian Process Molecule Property Prediction with FlowMO Henry B. Moss Ryan-Rhys Griffiths 21 23 0 02 Oct 2020
Few-shot Learning for Time-series Forecasting Tomoharu Iwata Atsutoshi Kumagai AI4TS 11 18 0 30 Sep 2020
Message Passing Neural Processes Ben Day Cătălina Cangea Arian R. Jamasb Pietro Lió 27 11 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 29 52 0 24 Sep 2020
Meta-Learning with Shared Amortized Variational Inference E. Iakovleva Jakob Verbeek Alahari Karteek OOD FedML BDL 26 22 0 27 Aug 2020
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables Q. Wang H. V. Hoof BDL 21 42 0 21 Aug 2020
Learning from Irregularly-Sampled Time Series: A Missing Data Perspective Steven Cheng-Xian Li Benjamin M. Marlin AI4TS 23 56 0 17 Aug 2020
Bootstrapping Neural Processes Juho Lee Yoonho Lee Jungtaek Kim Eunho Yang Sung Ju Hwang Yee Whye Teh UQCV BDL 26 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 Turner BDL 14 77 0 02 Jul 2020
Robustifying Sequential Neural Processes Jaesik Yoon Gautam Singh Sungjin Ahn 29 27 0 29 Jun 2020
Set Based Stochastic Subsampling Bruno Andreis Seanie Lee A. Nguyen Juho Lee Eunho Yang Sung Ju Hwang BDL 8 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 26 34 0 19 Jun 2020
MetaSDF: Meta-learning Signed Distance Functions Vincent Sitzmann E. R. Chan Richard Tucker Noah Snavely Gordon Wetzstein 33 247 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 47 2,486 0 17 Jun 2020
NP-PROV: Neural Processes with Position-Relevant-Only Variances Xuesong Wang Lina Yao Xianzhi Wang Feiping Nie BDL 26 3 0 15 Jun 2020
Task-similarity Aware Meta-learning through Nonparametric Kernel Regression Arun Venkitaraman Anders Hansson B. Wahlberg 25 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 27 34 0 11 Jun 2020
Neural Physicist: Learning Physical Dynamics from Image Sequences Baocheng Zhu Shijun Wang James Y. Zhang AI4CE 6 1 0 09 Jun 2020
Meta Learning as Bayes Risk Minimization S. Maeda Toshiki Nakanishi Masanori Koyama BDL 23 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 B. Hodjat 13 3 0 28 May 2020
Kernel Self-Attention in Deep Multiple Instance Learning Dawid Rymarczyk Adriana Borowa Jacek Tabor Bartosz Zieliñski SSL 14 5 0 25 May 2020
Differentiable Mapping Networks: Learning Structured Map Representations for Sparse Visual Localization Peter Karkus A. Angelova Vincent Vanhoucke Rico Jonschkowski 17 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 19 125 0 27 Apr 2020
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context Wenyu Zhang Skyler Seto Devesh K. Jha 20 5 0 26 Mar 2020
Energy-Based Processes for Exchangeable Data Mengjiao Yang Bo Dai H. Dai Dale Schuurmans 22 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 25 49 0 24 Feb 2020
Deep Fourier Kernel for Self-Attentive Point Processes Shixiang Zhu Minghe Zhang Ruyi Ding Yao Xie 3DPC 6 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 15 3 0 17 Feb 2020
Local Nonparametric Meta-Learning Wonjoon Goo S. Niekum 32 3 0 09 Feb 2020
Model Inversion Networks for Model-Based Optimization Aviral Kumar Sergey Levine OffRL 27 93 0 31 Dec 2019
MetaFun: Meta-Learning with Iterative Functional Updates Jin Xu Jean-François Ton Hyunjik Kim Adam R. Kosiorek Yee Whye Teh 22 68 0 05 Dec 2019
Convolutional Conditional Neural Processes Jonathan Gordon W. Bruinsma Andrew Y. K. Foong James Requeima Yann Dubois Richard Turner BDL 25 162 0 29 Oct 2019
Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process Jiacheng Zhu Shenghao Qin Wenshuo Wang Ding Zhao 22 10 0 17 Oct 2019
Recurrent Attentive Neural Process for Sequential Data Shenghao Qin Jiacheng Zhu Jimmy Qin Wenshuo Wang Ding Zhao BDL AI4TS 27 38 0 17 Oct 2019
Neural Approximation of an Auto-Regressive Process through Confidence Guided Sampling Y. Yoo Sanghyuk Chun Sangdoo Yun Jung-Woo Ha Jaejun Yoo 12 0 0 15 Oct 2019
Neural Multisensory Scene Inference Jae Hyun Lim Pedro H. O. Pinheiro Negar Rostamzadeh C. Pal Sungjin Ahn 14 10 0 06 Oct 2019
Wasserstein Neural Processes Andrew N. Carr Jared Nielson David Wingate BDL 17 2 0 01 Oct 2019
Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video Maria Bauzá Ferran Alet Yen-Chen Lin Tomas Lozano-Perez L. Kaelbling Phillip Isola Alberto Rodriguez 17 22 0 01 Oct 2019