Title
The Caltech Fish Counting Dataset: A Benchmark for Multiple-Object Tracking and Counting Justin Kay Peter Kulits Suzanne Stathatos Siqi Deng Erik Young Sara Beery Grant Van Horn Pietro Perona 27 26 0 19 Jul 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 60 71 0 19 Jul 2022
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift Ananya Kumar Tengyu Ma Percy Liang Aditi Raghunathan UQCV OODD OOD 45 38 0 18 Jul 2022
Feed-Forward Latent Domain Adaptation Ondrej Bohdal Da Li S. Hu Timothy M. Hospedales OOD 41 1 0 15 Jul 2022
Contrastive Adapters for Foundation Model Group Robustness Michael Zhang Christopher Ré VLM 18 62 0 14 Jul 2022
On the Strong Correlation Between Model Invariance and Generalization Weijian Deng Stephen Gould Liang Zheng OOD 32 16 0 14 Jul 2022
Leakage and the Reproducibility Crisis in ML-based Science Sayash Kapoor Arvind Narayanan 25 177 0 14 Jul 2022
Repairing Neural Networks by Leaving the Right Past Behind Ryutaro Tanno Melanie F. Pradier A. Nori Yingzhen Li KELM 33 31 0 11 Jul 2022
Back to the Source: Diffusion-Driven Test-Time Adaptation Jin Gao Jialing Zhang Xihui Liu Trevor Darrell Evan Shelhamer Dequan Wang TTA 13 51 0 07 Jul 2022
A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images Chengfeng Zhou Songchang Chen Chenming Xu Jun Wang Feng Liu Chun Zhang Juan Ye Hefeng Huang Xiaobo Li OOD 13 0 0 07 Jul 2022
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning Damien Teney Maxime Peyrard Ehsan Abbasnejad 38 29 0 06 Jul 2022
Generalization to translation shifts: a study in architectures and augmentations Suriya Gunasekar 13 1 0 05 Jul 2022
Predicting Out-of-Domain Generalization with Neighborhood Invariance Nathan Ng Neha Hulkund Kyunghyun Cho Marzyeh Ghassemi OOD 27 4 0 05 Jul 2022
Invariant and Transportable Representations for Anti-Causal Domain Shifts Yibo Jiang Victor Veitch OOD 129 32 0 04 Jul 2022
Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness Saeid Asgari Taghanaki A. Gholami Fereshte Khani Kristy Choi Linh-Tam Tran Ran Zhang Aliasghar Khani 14 0 0 04 Jul 2022
Identifying the Context Shift between Test Benchmarks and Production Data Matthew Groh OOD 21 8 0 03 Jul 2022
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection Marius Dragoi Elena Burceanu Emanuela Haller Andrei Manolache Florin Brad OOD 23 18 0 30 Jun 2022
Shifts 2.0: Extending The Dataset of Real Distributional Shifts A. Malinin A. Athanasopoulos M. Barakovic Meritxell Bach Cuadra Mark Gales ... Francesco La Rosa Eli Sivena V. Tsarsitalidis Efi Tsompopoulou E. Volf OOD 30 28 0 30 Jun 2022
Towards out of distribution generalization for problems in mechanics Lingxiao Yuan Harold S. Park Emma Lejeune OOD AI4CE 36 17 0 29 Jun 2022
Distilling Model Failures as Directions in Latent Space Saachi Jain Hannah Lawrence Ankur Moitra A. Madry 23 90 0 29 Jun 2022
Improved Text Classification via Test-Time Augmentation H. Lu Divya Shanmugam Harini Suresh John Guttag ViT 33 11 0 27 Jun 2022
Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift Christina Baek Yiding Jiang Aditi Raghunathan Zico Kolter 32 79 0 27 Jun 2022
Monitoring Shortcut Learning using Mutual Information Mohammed Adnan Yani Andrew Ioannou Chuan-Yung Tsai A. Galloway H. R. Tizhoosh Graham W. Taylor 25 6 0 27 Jun 2022
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization Bang An Zora Che Mucong Ding Furong Huang 22 31 0 26 Jun 2022
Gated Domain Units for Multi-source Domain Generalization Simon Foll Alina Dubatovka Eugen Ernst Siu Lun Chau Martin Maritsch Patrik Okanovic Gudrun Thater J. M. Buhmann Felix Wortmann Krikamol Muandet OOD 40 3 0 24 Jun 2022
Measuring Representational Robustness of Neural Networks Through Shared Invariances Vedant Nanda Till Speicher Camila Kolling John P. Dickerson Krishna P. Gummadi Adrian Weller 19 12 0 23 Jun 2022
Invariant Causal Mechanisms through Distribution Matching Mathieu Chevalley Charlotte Bunne Andreas Krause Stefan Bauer OOD CML 14 40 0 23 Jun 2022
Gradual Domain Adaptation via Normalizing Flows Shogo Sagawa H. Hino CLL OOD 22 10 0 23 Jun 2022
Test-time image-to-image translation ensembling improves out-of-distribution generalization in histopathology Marin Scalbert Maria Vakalopoulou Florent Couzinié-Devy 30 13 0 20 Jun 2022
Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifold Sebastian Ruder Ivan Vulić Anders Søgaard 41 29 0 20 Jun 2022
Adversarial Scrutiny of Evidentiary Statistical Software Rediet Abebe Moritz Hardt Angela Jin John Miller Ludwig Schmidt Rebecca Wexler 36 5 0 19 Jun 2022
How Robust is Unsupervised Representation Learning to Distribution Shift? Yuge Shi Imant Daunhawer Julia E. Vogt Philip Torr Amartya Sanyal OOD 35 25 0 17 Jun 2022
The Importance of Background Information for Out of Distribution Generalization Jupinder Parmar Khaled Kamal Saab Brian Pogatchnik D. Rubin Christopher Ré OOD 21 0 0 17 Jun 2022
GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui Xiner Li Limei Wang Shuiwang Ji OOD 33 116 0 16 Jun 2022
Noisy Learning for Neural ODEs Acts as a Robustness Locus Widening Martin Gonzalez H. Hajri Loic Cantat Mihaly Petreczky 37 1 0 16 Jun 2022
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency Viraj Prabhu Sriram Yenamandra Aaditya K. Singh Judy Hoffman 39 14 0 16 Jun 2022
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization Jivat Neet Kaur Emre Kıcıman Amit Sharma UQCV OOD 28 25 0 15 Jun 2022
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization Yongqiang Chen Kaiwen Zhou Yatao Bian Binghui Xie Bing Wu ... Kaili Ma Han Yang P. Zhao Bo Han James Cheng OOD OODD 11 34 0 15 Jun 2022
Improving Diversity with Adversarially Learned Transformations for Domain Generalization Tejas Gokhale Rushil Anirudh Jayaraman J. Thiagarajan B. Kailkhura Chitta Baral Yezhou Yang 27 28 0 15 Jun 2022
ABCinML: Anticipatory Bias Correction in Machine Learning Applications Abdulaziz A. Almuzaini C. Bhatt David M. Pennock V. Singh FaML 30 10 0 14 Jun 2022
Learning towards Synchronous Network Memorizability and Generalizability for Continual Segmentation across Multiple Sites Jingyang Zhang Peng Xue Ran Gu Yuning Gu Mianxin Liu Yongsheng Pan Zhiming Cui Jiawei Huang Lei Ma Dinggang Shen CLL 27 8 0 14 Jun 2022
Contrastive Learning for Unsupervised Domain Adaptation of Time Series Yilmazcan Ozyurt Stefan Feuerriegel Ce Zhang AI4TS 34 45 0 13 Jun 2022
CodeS: Towards Code Model Generalization Under Distribution Shift Qiang Hu Yuejun Guo Xiaofei Xie Maxime Cordy Lei Ma Mike Papadakis Yves Le Traon OOD 36 10 0 11 Jun 2022
Lost in Transmission: On the Impact of Networking Corruptions on Video Machine Learning Models Trenton Chang Daniel Y. Fu 20 0 0 10 Jun 2022
On the Generalization and Adaption Performance of Causal Models Nino Scherrer Anirudh Goyal Stefan Bauer Yoshua Bengio Nan Rosemary Ke CML OOD BDL TTA 31 8 0 09 Jun 2022
How unfair is private learning ? Amartya Sanyal Yaxian Hu Fanny Yang FaML FedML 33 22 0 08 Jun 2022
Toward Certified Robustness Against Real-World Distribution Shifts Haoze Wu Teruhiro Tagomori Alexander Robey Fengjun Yang Nikolai Matni George Pappas Hamed Hassani C. Păsăreanu Clark W. Barrett AAML OOD 47 18 0 08 Jun 2022
Robust Calibration with Multi-domain Temperature Scaling Yaodong Yu Stephen Bates Yi Ma Michael I. Jordan OOD UQCV 32 33 0 06 Jun 2022
AugLoss: A Robust Augmentation-based Fine Tuning Methodology Kyle Otstot J. Cava Tyler Sypherd Lalitha Sankar 26 0 0 05 Jun 2022
(Im)possibility of Collective Intelligence Krikamol Muandet 30 6 0 05 Jun 2022