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Workshop
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Solving Out-of-Distribution Challenges in Optical Foundation Models using Self-Improving Data Augmentation
Mingqian Ma · Taigao Ma · L. Jay Guo
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Workshop
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Evaluating Sparse Galaxy Simulations via Out-of-Distribution Detection and Amortized Bayesian Model Comparison
Lingyi Zhou · Stefan Radev · William H. Oliver · Aura Obreja · Zehao Jin · Tobias Buck
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Workshop
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Adapting Segment Anything Model (SAM) to Experimental Datasets via Fine-Tuning on GAN-based Simulation: A Case Study in Additive Manufacturing
Anika Tabassum · Amir K Ziabari
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Workshop
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Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
David Schnurr · Kai Helli · Noah Hollmann · Samuel Müller · Frank Hutter
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Workshop
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How to Determine the Preferred Image Distribution of a Black-Box Vision-Language Model?
Saeid Asgari · Joseph G Lambourne · Alana Mongkhounsavath
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Expo Talk Panel
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Wed 16:30
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Mastering Distributed Training: Best Practices for Scalable Model Training
· Corey Lowman
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Workshop
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Probabilistic Fusion Approach for Robust Battery Prognostics
Jokin Alcibar
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Workshop
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In-distribution adversarial attacks on object recognition models using gradient-free search.
Spandan Madan · Tomotake Sasaki · Tzu-Mao Li · Hanspeter Pfister · Xavier Boix
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Poster
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Fri 16:30
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Shaping the distribution of neural responses with interneurons in a recurrent circuit model
David Lipshutz · Eero Simoncelli
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Workshop
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Sat 12:00
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Distribution-based sensitivity analysis for large language models
Paulius Rauba · Qiyao Wei · Mihaela van der Schaar
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Poster
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Thu 16:30
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Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model
Jing Zhang · Linjiajie Fang · Kexin SHI · Wenjia Wang · Bingyi Jing
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Poster
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Wed 16:30
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Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation
Dombry Clement · Ahmed Zaoui
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