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Workshop
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SCENE-Net V2: Interpretable Multiclass 3D Scene Understanding with Geometric Priors
Diogo Lavado · Claudia Soares · Alessandra Micheletti
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Workshop
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Identifying Biological Priors and Structure in Single-Cell Foundation Models
Flavia Pedrocchi · Stefan Stark · Gunnar Ratsch · Amir Joudaki
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Workshop
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DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning
Zijian Zhou · Xiaoqiang Lin · Xinyi Xu · Alok Prakash · Daniela Rus · Bryan Kian Hsiang Low
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Workshop
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A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning
Eura Nofshin · Esther Brown · Brian Lim · Weiwei Pan · Finale Doshi-Velez
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Workshop
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Generative Design of Decision Tree Policies for Reinforcement Learning
Jacob Pettit · Chak Shing Lee · Jiachen Yang · Alex Ho · Daniel Faissol · Brenden Petersen · Mikel Landajuela
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Workshop
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Explaining the Model, Protecting Your Data: Revealing and Mitigating the Data Privacy Risks of Post-Hoc Model Explanations via Membership Inference
Catherine Huang · Martin Pawelczyk · Himabindu Lakkaraju
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Workshop
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Sat 1:00
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Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels
Zhuorui Ye · Stephanie Milani · Fei Fang · Geoff Gordon
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Workshop
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Fri 8:00
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Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels
Zhuorui Ye · Stephanie Milani · Fei Fang · Geoff Gordon
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Workshop
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How Consensus-Based Optimization can be Interpreted as a Stochastic Relaxation of Gradient Descent
Konstantin Riedl · Timo Klock · Carina Geldhauser · Massimo Fornasier
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Poster
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Thu 4:30
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Towards Compositionality in Concept Learning
Adam Stein · Aaditya Naik · Yinjun Wu · Mayur Naik · Eric Wong
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Workshop
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Manipulating Feature Visualizations with Gradient Slingshots
Dilyara Bareeva · Marina Höhne · Alexander Warnecke · Lukas Pirch · Klaus-robert Mueller · Konrad Rieck · Kirill Bykov
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Poster
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Thu 2:30
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Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee
George Chen
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