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Conditional Neural Processes

Conditional Neural Processes

International Conference on Machine Learning (ICML), 2018
4 July 2018
M. Garnelo
Dan Rosenbaum
Chris J. Maddison
Tiago Ramalho
D. Saxton
Murray Shanahan
Yee Whye Teh
Danilo Jimenez Rezende
S. M. Ali Eslami
    UQCVBDL
ArXiv (abs)PDFHTML

Papers citing "Conditional Neural Processes"

50 / 447 papers shown
Where to Measure: Epistemic Uncertainty-Based Sensor Placement with ConvCNPs
Where to Measure: Epistemic Uncertainty-Based Sensor Placement with ConvCNPs
Feyza Eksen
Stefan Oehmcke
Stefan Lüdtke
85
0
0
27 Nov 2025
Can Synthetic Data Improve Symbolic Regression Extrapolation Performance?
Can Synthetic Data Improve Symbolic Regression Extrapolation Performance?
Fitria Wulandari Ramlan
C. O'Riordan
Gabriel Kronberger
James McDermott
SyDa
143
0
0
27 Nov 2025
MIST: Mutual Information Estimation Via Supervised Training
MIST: Mutual Information Estimation Via Supervised Training
German Gritsai
Megan Richards
Maxime Méloux
Kyunghyun Cho
Maxime Peyrard
OOD
385
0
0
24 Nov 2025
Resolving Node Identifiability in Graph Neural Processes via Laplacian Spectral Encodings
Resolving Node Identifiability in Graph Neural Processes via Laplacian Spectral Encodings
Zimo Yan
Zheng Xie
Chang-rui Liu
Y. X. R. Wang
151
2
0
24 Nov 2025
Parametric Pareto Set Learning for Expensive Multi-Objective Optimization
Parametric Pareto Set Learning for Expensive Multi-Objective Optimization
Ji Cheng
Bo Xue
Qingfu Zhang
149
1
0
08 Nov 2025
Context-aware Learned Mesh-based Simulation via Trajectory-Level Meta-Learning
Context-aware Learned Mesh-based Simulation via Trajectory-Level Meta-Learning
Philipp Dahlinger
Niklas Freymuth
Tai Hoang
Tobias Würth
Michael Volpp
Luise Kärger
Gerhard Neumann
AI4CE
359
1
0
07 Nov 2025
Conjugate Relation Modeling for Few-Shot Knowledge Graph Completion
Conjugate Relation Modeling for Few-Shot Knowledge Graph Completion
Zilong Wang
Qingtian Zeng
Hua Duan
Cheng Cheng
Minghao Zou
Ziyang Wang
129
0
0
26 Oct 2025
Neural Variational Dropout Processes
Neural Variational Dropout ProcessesInternational Conference on Learning Representations (ICLR), 2025
Insu Jeon
Youngjin Park
Gunhee Kim
BDLUQCV
357
3
0
22 Oct 2025
PriorGuide: Test-Time Prior Adaptation for Simulation-Based Inference
PriorGuide: Test-Time Prior Adaptation for Simulation-Based Inference
Yang Yang
Severi Rissanen
Paul E. Chang
Nasrulloh Loka
Daolang Huang
Arno Solin
Markus Heinonen
Luigi Acerbi
185
1
0
15 Oct 2025
Progressive multi-fidelity learning with neural networks for physical system predictions
Progressive multi-fidelity learning with neural networks for physical system predictions
Paolo Conti
Mengwu Guo
A. Frangi
Andrea Manzoni
AI4CE
151
1
0
15 Oct 2025
Vision-LLMs for Spatiotemporal Traffic Forecasting
Vision-LLMs for Spatiotemporal Traffic Forecasting
Ning Yang
Hengyu Zhong
Haijun Zhang
Randall Berry
AI4TS
178
1
0
13 Oct 2025
Placeit! A Framework for Learning Robot Object Placement Skills
Placeit! A Framework for Learning Robot Object Placement Skills
Amina Ferrad
J. Huber
Francois Helenon
Julien Gleyze
Mahdi Khoramshahi
Stéphane Doncieux
177
2
0
10 Oct 2025
MaNGO - Adaptable Graph Network Simulators via Meta-Learning
MaNGO - Adaptable Graph Network Simulators via Meta-Learning
Philipp Dahlinger
Tai Hoang
Denis Blessing
Niklas Freymuth
Gerhard Neumann
AI4CE
297
3
0
07 Oct 2025
Multi-task Neural Diffusion Processes
Multi-task Neural Diffusion Processes
Joseph Rawson
Domniki Ladopoulou
Petros Dellaportas
DiffM
195
0
0
03 Oct 2025
Task-Level Contrastiveness for Cross-Domain Few-Shot Learning
Task-Level Contrastiveness for Cross-Domain Few-Shot Learning
Kristi Topollai
A. Choromańska
189
0
0
03 Oct 2025
Fine-Tuning Flow Matching via Maximum Likelihood Estimation of Reconstructions
Fine-Tuning Flow Matching via Maximum Likelihood Estimation of Reconstructions
Zhaoyi Li
Jingtao Ding
Yong Li
Shihua Li
286
0
0
02 Oct 2025
A Multi-Scale Graph Neural Process with Cross-Drug Co-Attention for Drug-Drug Interactions Prediction
A Multi-Scale Graph Neural Process with Cross-Drug Co-Attention for Drug-Drug Interactions Prediction
Zimo Yan
Jie Zhang
Zheng Xie
Y. Song
Hao Li
142
2
0
18 Sep 2025
Spatiotemporal graph neural process for reconstruction, extrapolation, and classification of cardiac trajectories
Spatiotemporal graph neural process for reconstruction, extrapolation, and classification of cardiac trajectories
Jaume Banus
Augustin C. Ogier
Roger Hullin
Philippe Meyer
Ruud B. van Heeswijk
Jonas Richiardi
217
0
0
16 Sep 2025
Conformal Prediction for Time-series Forecasting with Change Points
Conformal Prediction for Time-series Forecasting with Change Points
S. Sun
Rose Yu
AI4TS
526
2
0
02 Sep 2025
Distance-informed Neural Processes
Distance-informed Neural Processes
Aishwarya Venkataramanan
Joachim Denzler
UQCVBDL
205
1
0
26 Aug 2025
Probabilistic Pretraining for Neural Regression
Probabilistic Pretraining for Neural Regression
Boris N. Oreshkin
Shiv Tavker
Dmitry Efimov
UQCVBDL
292
0
0
22 Aug 2025
Uncertainty Propagation Networks for Neural Ordinary Differential Equations
Uncertainty Propagation Networks for Neural Ordinary Differential Equations
Hadi Jahanshahi
Zheng H. Zhu
184
1
0
22 Aug 2025
Compressive Meta-Learning
Compressive Meta-Learning
D. M. Montserrat
David Bonet
Maria Perera
Xavier Giró-i-Nieto
A. Ioannidis
123
1
0
14 Aug 2025
Neural Bridge Processes
Neural Bridge Processes
Jian Xu
Y. Liu
Qibin Zhao
John Paisley
Delu Zeng
DiffM
1.3K
0
0
10 Aug 2025
MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling
MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling
E. L. Naour
Tahar Nabil
G. Agoua
AI4TS
289
1
0
17 Jul 2025
Warm Starts Accelerate Conditional Diffusion
Warm Starts Accelerate Conditional Diffusion
Jonas Scholz
Richard Turner
DiffMVLMAI4CE
197
0
0
12 Jul 2025
Tractable Representation Learning with Probabilistic Circuits
Tractable Representation Learning with Probabilistic Circuits
Steven Braun
Sahil Sidheekh
Antonio Vergari
Martin Mundt
S. Natarajan
Kristian Kersting
TPM
529
4
0
06 Jul 2025
LSCD: Lomb-Scargle Conditioned Diffusion for Time series Imputation
LSCD: Lomb-Scargle Conditioned Diffusion for Time series Imputation
Elizabeth Fons
Alejandro Sztrajman
Yousef El-Laham
Luciana Ferrer
Svitlana Vyetrenko
Manuela Veloso
AI4TS
244
4
0
20 Jun 2025
Quantum-Inspired Differentiable Integral Neural Networks (QIDINNs): A Feynman-Based Architecture for Continuous Learning Over Streaming Data
Quantum-Inspired Differentiable Integral Neural Networks (QIDINNs): A Feynman-Based Architecture for Continuous Learning Over Streaming Data
Oscar Boullosa Dapena
263
0
0
13 Jun 2025
Neural Functions for Learning Periodic Signal
Neural Functions for Learning Periodic SignalInternational Conference on Learning Representations (ICLR), 2025
Woojin Cho
Minju Jo
Kookjin Lee
Noseong Park
316
2
0
11 Jun 2025
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning
Toby Boyne
Juan S. Campos
Becky D Langdon
Jixiang Qing
Yilin Xie
...
Kim E. Jelfs
Sarah Boyall
Thomas M. Dixon
Linden Schrecker
Jose Pablo Folch
241
2
0
09 Jun 2025
CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
Vahid Balazadeh
Hamidreza Kamkari
Valentin Thomas
Benson Li
Junwei Ma
Jesse C. Cresswell
Rahul G. Krishnan
CML
266
19
0
09 Jun 2025
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
Rong-Xi Tan
Ming Chen
Ke Xue
Yao Wang
Yaoyuan Wang
Sheng Fu
Chao Qian
OffRL
283
5
0
08 Jun 2025
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
Daolang Huang
Xinyi Wen
Ayush Bharti
Samuel Kaski
Luigi Acerbi
265
2
0
08 Jun 2025
Do-PFN: In-Context Learning for Causal Effect Estimation
Do-PFN: In-Context Learning for Causal Effect Estimation
Jake Robertson
Arik Reuter
Siyuan Guo
Noah Hollmann
Katharina Eggensperger
Bernhard Schölkopf
CML
542
21
0
06 Jun 2025
Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction
Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction
Zesheng Ye
C. Cai
Ruijiang Dong
Jianzhong Qi
Bingquan Shen
Pin-Yu Chen
Feng Liu
805
3
0
05 Jun 2025
Unsupervised Meta-Testing with Conditional Neural Processes for Hybrid Meta-Reinforcement Learning
Unsupervised Meta-Testing with Conditional Neural Processes for Hybrid Meta-Reinforcement LearningIEEE Robotics and Automation Letters (RA-L), 2024
S. E. Ada
Emre Ugur
BDL
338
6
0
04 Jun 2025
Position: The Future of Bayesian Prediction Is Prior-Fitted
Position: The Future of Bayesian Prediction Is Prior-Fitted
Samuel G. Müller
Arik Reuter
Noah Hollmann
David Rügamer
Katharina Eggensperger
345
10
0
29 May 2025
Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling
Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling
Gustavo Sutter Pessurno de Carvalho
Mohammed Abdulrahman
Hao Wang
Sriram Ganapathi Subramanian
Marc St-Aubin
Sharon O'Sullivan
Lawrence Wan
Luis Ricardez-Sandoval
Pascal Poupart
Agustinus Kristiadi
357
1
0
29 May 2025
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RLInternational Conference on Learning Representations (ICLR), 2025
Yu-Heng Hung
Kai-Jie Lin
Yu-Heng Lin
Chien-Yi Wang
Cheng Sun
Ping-Chun Hsieh
387
6
0
28 May 2025
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review
Chengmin Zhou
Ville Kyrki
Pasi Fränti
Laura Ruotsalainen
BDLAI4CE
536
1
0
12 May 2025
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu
Pan Zhou
Zehao Xiao
Jiayi Shen
Wenzhe Yin
Jan-Jakob Sonke
E. Gavves
401
2
0
03 May 2025
Enhancing System Self-Awareness and Trust of AI: A Case Study in Trajectory Prediction and Planning
Enhancing System Self-Awareness and Trust of AI: A Case Study in Trajectory Prediction and Planning
Lars Ullrich
Zurab Mujirishvili
Knut Graichen
289
2
0
25 Apr 2025
MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design
MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design
Zimo Yan
Jie Zhang
Zheng Xie
Chang-rui Liu
Wenshu Fan
Yiping Song
513
2
0
22 Apr 2025
Exploring Pseudo-Token Approaches in Transformer Neural Processes
Exploring Pseudo-Token Approaches in Transformer Neural Processes
Jose Lara-Rangel
Nanze Chen
Fengzhe Zhang
263
1
0
19 Apr 2025
Sparse Gaussian Neural Processes
Sparse Gaussian Neural ProcessesSymposium on Advances in Approximate Bayesian Inference (AABI), 2025
Tommy Rochussen
Vincent Fortuin
BDLUQCV
500
2
0
02 Apr 2025
Conditional Temporal Neural Processes with Covariance Loss
Conditional Temporal Neural Processes with Covariance LossInternational Conference on Machine Learning (ICML), 2025
Boseon Yoo
Jiwoo Lee
Janghoon Ju
Seijun Chung
Soyeon Kim
Jaesik Choi
386
19
0
01 Apr 2025
Offline Model-Based Optimization: Comprehensive Review
Offline Model-Based Optimization: Comprehensive Review
Minsu Kim
Jiayao Gu
Ye Yuan
Taeyoung Yun
Ziqiang Liu
Yoshua Bengio
Can Chen
OffRL
493
18
0
21 Mar 2025
On the Limits of Applying Graph Transformers for Brain Connectome Classification
On the Limits of Applying Graph Transformers for Brain Connectome Classification
Jose Lara-Rangel
Clare Heinbaugh
410
0
0
20 Mar 2025
Meta Learning not to Learn: Robustly Informing Meta-Learning under Nuisance-Varying Families
Meta Learning not to Learn: Robustly Informing Meta-Learning under Nuisance-Varying Families
Louis McConnell
OODCML
340
0
0
06 Mar 2025
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