Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling

9 July 2022

Papers citing "Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling"

50 / 71 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 25 0 0 03 May 2025
Exploring Pseudo-Token Approaches in Transformer Neural Processes Jose Lara-Rangel Nanze Chen Fengzhe Zhang 22 0 0 19 Apr 2025
Sparse Gaussian Neural Processes Tommy Rochussen Vincent Fortuin BDL UQCV 54 0 0 02 Apr 2025
Architectural and Inferential Inductive Biases For Exchangeable Sequence Modeling Daksh Mittal Ang Li Tzu-Ching Yen Daniel Guetta Hongseok Namkoong 45 0 0 03 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 44 0 0 28 Feb 2025
Vector-ICL: In-context Learning with Continuous Vector Representations Yufan Zhuang Chandan Singh Liyuan Liu Jingbo Shang Jianfeng Gao 52 3 0 21 Feb 2025
Geometric Neural Process Fields Wenzhe Yin Zehao Xiao Jiayi Shen Yunlu Chen Cees G. M. Snoek J. Sonke E. Gavves AI4CE 38 0 0 04 Feb 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 44 1 0 03 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 41 4 0 20 Oct 2024
Predicting from Strings: Language Model Embeddings for Bayesian Optimization Tung Nguyen Qiuyi Zhang Bangding Yang Chansoo Lee J. Bornschein Yingjie Miao Sagi Perel Yutian Chen Xingyou Song BDL 18 3 0 14 Oct 2024
Metalic: Meta-Learning In-Context with Protein Language Models Jacob Beck Shikha Surana Manus McAuliffe Oliver Bent Thomas D. Barrett Juan Jose Garau Luis Paul Duckworth AI4CE 28 0 0 10 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
GAMformer: In-Context Learning for Generalized Additive Models Andreas Mueller Julien N. Siems Harsha Nori David Salinas Arber Zela Rich Caruana Frank Hutter AI4CE 31 3 0 06 Oct 2024
Towards certifiable AI in aviation: landscape, challenges, and opportunities Hymalai Bello Daniel Geißler L. Ray Stefan Muller-Divéky Peter Muller Shannon Kittrell Mengxi Liu Bo Zhou Paul Lukowicz 21 1 0 13 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 14 0 0 14 Aug 2024
LICO: Large Language Models for In-Context Molecular Optimization Tung Nguyen Aditya Grover 28 6 0 27 Jun 2024
In-Context In-Context Learning with Transformer Neural Processes Matthew Ashman Cristiana-Diana Diaconu Adrian Weller Richard E. Turner 18 3 0 19 Jun 2024
Approximately Equivariant Neural Processes Matthew Ashman Cristiana-Diana Diaconu Adrian Weller W. Bruinsma Richard E. Turner BDL 32 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 33 4 0 18 Jun 2024
Probing the Decision Boundaries of In-context Learning in Large Language Models Siyan Zhao Tung Nguyen Aditya Grover 32 6 0 17 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 38 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
Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching Fernando Moreno-Pino Alvaro Arroyo H. Waldon Xiaowen Dong Álvaro Cartea AI4TS 27 1 0 31 May 2024
Data-Driven Simulator for Mechanical Circulatory Support with Domain Adversarial Neural Process S. Sun Wenyuan Chen Zihao Zhou Sonia Fereidooni Elise Jortberg Rose Yu AI4CE 29 0 0 28 May 2024
Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation Dong Bok Lee Aoxuan Silvia Zhang Byung-Hoon Kim Junhyeon Park Juho Lee Sung Ju Hwang Haebeom Lee 27 1 0 28 May 2024
Rényi Neural Processes Xuesong Wang He Zhao Edwin V. Bonilla UQCV BDL 25 0 0 25 May 2024
Position: Leverage Foundational Models for Black-Box Optimization Xingyou Song Yingtao Tian Robert Tjarko Lange Chansoo Lee Yujin Tang Yutian Chen 38 5 0 06 May 2024
Spectral Convolutional Conditional Neural Processes Peiman Mohseni Nick Duffield 19 3 0 19 Apr 2024
All-in-one simulation-based inference Manuel Gloeckler Michael Deistler Christian Weilbach Frank D. Wood Jakob H. Macke 19 25 0 15 Apr 2024
Real-time Adaptation for Condition Monitoring Signal Prediction using Label-aware Neural Processes Seokhyun Chung Raed Al Kontar 26 0 0 25 Mar 2024
Rough Transformers for Continuous and Efficient Time-Series Modelling Fernando Moreno-Pino Alvaro Arroyo H. Waldon Xiaowen Dong Álvaro Cartea AI4TS MedIm 23 5 0 15 Mar 2024
Reinforced In-Context Black-Box Optimization Lei Song Chenxiao Gao Ke Xue Chenyang Wu Dong Li Jianye Hao Zongzhang Zhang Chao Qian 24 3 0 27 Feb 2024
Cumulative Distribution Function based General Temporal Point Processes Maolin Wang Yu Pan Zenglin Xu Ruocheng Guo Xiangyu Zhao Wanyu Wang Yiqi Wang Zitao Liu Langming Liu AI4TS 9 0 0 01 Feb 2024
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors Wasu Top Piriyakulkij Yingheng Wang Volodymyr Kuleshov DiffM 25 1 0 05 Jan 2024
Diffusion Models With Learned Adaptive Noise S. Sahoo Aaron Gokaslan Christopher De Sa Volodymyr Kuleshov DiffM 21 8 0 20 Dec 2023
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation Tomoharu Iwata Atsutoshi Kumagai BDL UQCV 9 1 0 13 Dec 2023
ExPT: Synthetic Pretraining for Few-Shot Experimental Design Tung Nguyen Sudhanshu Agrawal Aditya Grover 11 14 0 30 Oct 2023
Episodic Multi-Task Learning with Heterogeneous Neural Processes Jiayi Shen Xiantong Zhen Qi Qi Wang M. Worring 9 11 0 28 Oct 2023
Group Preference Optimization: Few-Shot Alignment of Large Language Models Siyan Zhao John Dang Aditya Grover 13 28 0 17 Oct 2023
Tree Cross Attention Zixuan Chen Zewei He Ziqian Lu Zheming Lu Mohamed Osama Ahmed 34 0 0 29 Sep 2023
Exploiting Inferential Structure in Neural Processes Dharmesh Tailor Mohammad Emtiyaz Khan Eric Nalisnick BDL 26 1 0 27 Jun 2023
Supervised Pretraining Can Learn In-Context Reinforcement Learning Jonathan Lee Annie Xie Aldo Pacchiano Yash Chandak Chelsea Finn Ofir Nachum Emma Brunskill OffRL 19 73 0 26 Jun 2023
Constant Memory Attention Block Leo Feng Frederick Tung Hossein Hajimirsadeghi Yoshua Bengio Mohamed Osama Ahmed 12 0 0 21 Jun 2023
Practical Equivariances via Relational Conditional Neural Processes Daolang Huang Manuel Haussmann Ulpu Remes S. T. John Grégoire Clarté K. Luck Samuel Kaski Luigi Acerbi BDL 48 8 0 19 Jun 2023
Diffusion Models for Black-Box Optimization S. Krishnamoorthy Satvik Mashkaria Aditya Grover DiffM 13 50 0 12 Jun 2023
Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models Siyan Zhao Aditya Grover OffRL 6 7 0 09 Jun 2023
Taylorformer: Probabilistic Predictions for Time Series and other Processes Omer Nivron R. Parthipan Damon J. Wischik BDL AI4TS 11 2 0 30 May 2023
Adaptive Conditional Quantile Neural Processes Peiman Mohseni N. Duffield Bani Mallick Arman Hasanzadeh 14 3 0 30 May 2023