Papers
11,951 papers found
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks
Andrea Cini, Ivan Marisca, Cesare Alippi
FILM: Following Instructions in Language with Modular Methods
So Yeon Min, Devendra Singh Chaplot, Pradeep Kumar Ravikumar et al.
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space
Steeven JANNY, Fabien Baradel, Natalia Neverova et al.
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models
Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina et al.
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks
Anne Harrington, Arturo Deza
Fine-grained Differentiable Physics: A Yarn-level Model for Fabrics
Deshan Gong, Zhanxing Zhu, Andrew J. Bulpitt et al.
Finetuned Language Models are Zero-Shot Learners
Jason Wei, Maarten Bosma, Vincent Zhao et al.
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution
Ananya Kumar, Aditi Raghunathan, Robbie Matthew Jones et al.
Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward
FNU Hairi, Jia Liu, Songtao Lu
Fixed Neural Network Steganography: Train the images, not the network
Varsha Kishore, Xiangyu Chen, Yan Wang et al.
FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes
David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak et al.
Focus on the Common Good: Group Distributional Robustness Follows
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi
Fooling Explanations in Text Classifiers
Adam Ivankay, Ivan Girardi, Chiara Marchiori et al.
Fortuitous Forgetting in Connectionist Networks
Hattie Zhou, Ankit Vani, Hugo Larochelle et al.
FP-DETR: Detection Transformer Advanced by Fully Pre-training
Wen Wang, Yang Cao, Jing Zhang et al.
Frame Averaging for Invariant and Equivariant Network Design
Omri Puny, Matan Atzmon, Edward J. Smith et al.
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits
Yan Li, Dhruv Choudhary, Xiaohan Wei et al.
From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation
Da Xu, Yuting Ye, Chuanwei Ruan et al.
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness
Lingxiao Zhao, Wei Jin, Leman Akoglu et al.
GATSBI: Generative Adversarial Training for Simulation-Based Inference
Poornima Ramesh, Jan-Matthis Lueckmann, Jan Boelts et al.
Gaussian Mixture Convolution Networks
Adam Celarek, Pedro Hermosilla, Bernhard Kerbl et al.
GDA-AM: ON THE EFFECTIVENESS OF SOLVING MIN-IMAX OPTIMIZATION VIA ANDERSON MIXING
Huan He, Shifan Zhao, Yuanzhe Xi et al.
GeneDisco: A Benchmark for Experimental Design in Drug Discovery
Arash Mehrjou, Ashkan Soleymani, Andrew Jesson et al.
Generalisation in Lifelong Reinforcement Learning through Logical Composition
Geraud Nangue Tasse, Steven James, Benjamin Rosman
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects
Fredrik D. Johansson, Uri Shalit, Nathan Kallus et al.