Attentive Neural Processes

17 January 2019

Hyunjik Kim

A. Mnih

Jonathan Richard Schwarz

Papers citing "Attentive Neural Processes"

50 / 266 papers shown

Title
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes Jie Liu Pan Zhou Zehao Xiao Jiayi Shen Wenzhe Yin J. Sonke E. Gavves 31 0 0 03 May 2025
LoC-LIC: Low Complexity Learned Image Coding Using Hierarchical Feature Transforms Ayman A. Ameen Thomas Richter André Kaup 49 0 0 30 Apr 2025
Learning Attentive Neural Processes for Planning with Pushing Actions Atharv Jain Seiji Shaw Nicholas Roy 119 0 0 24 Apr 2025
MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design Zimo Yan Jie Zhang Zheng Xie Chang-rui Liu Y. Liu Yiping Song 36 0 0 22 Apr 2025
Exploring Pseudo-Token Approaches in Transformer Neural Processes Jose Lara-Rangel Nanze Chen Fengzhe Zhang 27 0 0 19 Apr 2025
Representation Learning for Tabular Data: A Comprehensive Survey Jun-Peng Jiang Si-Yang Liu Hao-Run Cai Qile Zhou Han-Jia Ye LMTD 46 0 0 17 Apr 2025
Sparse Gaussian Neural Processes Tommy Rochussen Vincent Fortuin BDL UQCV 56 0 0 02 Apr 2025
Meta Learning not to Learn: Robustly Informing Meta-Learning under Nuisance-Varying Families Louis McConnell OOD CML 50 0 0 06 Mar 2025
PABBO: Preferential Amortized Black-Box Optimization Xinyu Zhang Daolang Huang Samuel Kaski Julien Martinelli 34 0 0 02 Mar 2025
Dimension Agnostic Neural Processes Hyungi Lee Chaeyun Jang Dongbok Lee Juho Lee UQCV AI4CE 49 0 0 28 Feb 2025
Foundation Inference Models for Stochastic Differential Equations: A Transformer-based Approach for Zero-shot Function Estimation Patrick Seifner K. Cvejoski David Berghaus C. Ojeda Ramses J. Sanchez DiffM 48 1 0 26 Feb 2025
Compact Latent Representation for Image Compression (CLRIC) Ayman A. Ameen Thomas Richter André Kaup 54 0 0 24 Feb 2025
Amortized In-Context Bayesian Posterior Estimation Sarthak Mittal Niels Leif Bracher Guillaume Lajoie P. Jaini Marcus A. Brubaker 62 1 0 10 Feb 2025
Geometric Neural Process Fields Wenzhe Yin Zehao Xiao Jiayi Shen Yunlu Chen Cees G. M. Snoek J. Sonke E. Gavves AI4CE 41 0 0 04 Feb 2025
Stochastic Process Learning via Operator Flow Matching Yaozhong Shi Zachary E. Ross D. Asimaki Kamyar Azizzadenesheli 46 1 0 10 Jan 2025
DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting Daojun Liang Haixia Zhang Dongfeng Yuan UQCV 74 0 0 08 Jan 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
Robust Neural Processes for Noisy Data Chen Shapira Dan Rosenbaum 24 1 0 03 Nov 2024
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference Paul E. Chang Nasrulloh Loka Daolang Huang Ulpu Remes Samuel Kaski Luigi Acerbi AI4CE 49 4 0 20 Oct 2024
Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data Matthew Ashman Cristiana-Diana Diaconu Eric Langezaal Adrian Weller Richard E. Turner AI4TS 36 1 0 09 Oct 2024
Active Evaluation Acquisition for Efficient LLM Benchmarking Yang Li Jie Ma Miguel Ballesteros Yassine Benajiba Graham Horwood ELM 29 1 0 08 Oct 2024
Contextual Document Embeddings John X. Morris Alexander M. Rush 19 7 0 03 Oct 2024
Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks Alfredo Reichlin Gustaf Tegnér Miguel Vasco Hang Yin Mårten Björkman Danica Kragic 31 0 0 02 Oct 2024
Expanding Expressivity in Transformer Models with MöbiusAttention Anna-Maria Halacheva M. Nayyeri Steffen Staab 25 1 0 08 Sep 2024
An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems Taeyoung Yun Kanghoon Lee Sujin Yun Ilmyung Kim Won-Woo Jung Min-Cheol Kwon Kyujin Choi Yoohyeon Lee Jinkyoo Park 21 0 0 14 Aug 2024
Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation Cheems Wang Yiqin Lv Yixiu Mao Yun Qu Yi Tian Xu Xiangyang Ji OOD TTA 53 6 0 28 Jul 2024
In-Context In-Context Learning with Transformer Neural Processes Matthew Ashman Cristiana-Diana Diaconu Adrian Weller Richard E. Turner 26 3 0 19 Jun 2024
Approximately Equivariant Neural Processes Matthew Ashman Cristiana-Diana Diaconu Adrian Weller W. Bruinsma Richard E. Turner BDL 36 1 0 19 Jun 2024
Translation Equivariant Transformer Neural Processes Matthew Ashman Cristiana-Diana Diaconu Junhyuck Kim Lakee Sivaraya Stratis Markou James Requeima W. Bruinsma Richard E. Turner 46 4 0 18 Jun 2024
Estimating the Hallucination Rate of Generative AI Andrew Jesson Nicolas Beltran-Velez Quentin Chu Sweta Karlekar Jannik Kossen Yarin Gal John P. Cunningham David M. Blei 46 6 0 11 Jun 2024
System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization Jixiang Qing Becky D Langdon Robert M. Lee B. Shafei Mark van der Wilk Calvin Tsay Ruth Misener 32 1 0 04 Jun 2024
FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation Kun Chen Tao Chen Peng Ye Hao Chen Kang Chen Tao Han Wanli Ouyang Lei Bai 25 1 0 03 Jun 2024
Does learning the right latent variables necessarily improve in-context learning? Sarthak Mittal Eric Elmoznino Léo Gagnon Sangnie Bhardwaj Dhanya Sridhar Guillaume Lajoie 32 4 0 29 May 2024
Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space Peiyu Yu Dinghuai Zhang Hengzhi He Xiaojian Ma Ruiyao Miao ... Deqian Kong Ruiqi Gao Jianwen Xie Guang Cheng Ying Nian Wu 48 5 0 27 May 2024
Rényi Neural Processes Xuesong Wang He Zhao Edwin V. Bonilla UQCV BDL 32 0 0 25 May 2024
Spectral Convolutional Conditional Neural Processes Peiman Mohseni Nick Duffield 32 3 0 19 Apr 2024
On permutation-invariant neural networks Masanari Kimura Ryotaro Shimizu Yuki Hirakawa Ryosuke Goto Yuki Saito OOD AAML 38 12 0 26 Mar 2024
Real-time Adaptation for Condition Monitoring Signal Prediction using Label-aware Neural Processes Seokhyun Chung Raed Al Kontar 34 0 0 25 Mar 2024
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs S. C. Mouli Danielle C. Maddix S. Alizadeh Gaurav Gupta Andrew Stuart Michael W. Mahoney Yuyang Wang UQCV AI4CE 40 2 0 15 Mar 2024
Online Adaptation of Language Models with a Memory of Amortized Contexts Jihoon Tack Jaehyung Kim Eric Mitchell Jinwoo Shin Yee Whye Teh Jonathan Richard Schwarz KELM 47 18 0 07 Mar 2024
Learning to Defer to a Population: A Meta-Learning Approach Dharmesh Tailor Aditya Patra Rajeev Verma Putra Manggala Eric Nalisnick 20 9 0 05 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 27 2 0 29 Feb 2024
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings Kevin Frans Seohong Park Pieter Abbeel Sergey Levine OffRL 42 10 0 27 Feb 2024
Beyond Kalman Filters: Deep Learning-Based Filters for Improved Object Tracking Momir Adzemovic Predrag Tadić Andrija Petrović Mladen Nikolic 31 4 0 15 Feb 2024
Towards Generative Abstract Reasoning: Completing Raven's Progressive Matrix via Rule Abstraction and Selection Fan Shi Bin Li Xiangyang Xue ReLM LRM 31 1 0 18 Jan 2024
Space and Time Continuous Physics Simulation From Partial Observations Steeven Janny Madiha Nadri Wolf Julie Digne Christian Wolf AI4CE 34 5 0 17 Jan 2024
Towards Context-Aware Domain Generalization: Understanding the Benefits and Limits of Marginal Transfer Learning Jens Müller Lars Kühmichel Martin Rohbeck Stefan T. Radev Ullrich Kothe OOD 34 0 0 15 Dec 2023
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation Tomoharu Iwata Atsutoshi Kumagai BDL UQCV 22 1 0 13 Dec 2023
Target-Free Compound Activity Prediction via Few-Shot Learning Peter Eckmann Jake Anderson Michael K. Gilson Rose Yu 11 1 0 27 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