8 hours ago · I am looking for help. I decided to change my term course (12-14 weeks-long) on `introduction to Bayesian modeling with some hierarchical modeling' (no, that's ...
22 hours ago · Which neural networks are similar is a fundamental question for both machine learning and neuroscience. Our novel method compares representations based on ...
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24 hours ago · In this work, we propose a method to automate single-track experiments with three main objectives: (i) sample diversity; (ii) resource efficiency; and (iii) ...
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1 hour ago · Often it's about assessing the extent to which assumptions hold in real world settings where models are applied. My interest in theoretical work on calibration ...
20 hours ago · Which neural networks are similar is a fundamental question for both machine learning and neuroscience. Our novel method compares representations based on.
10 hours ago · This study aims to investigate how different risk and performance presentations for probabilistic predictions affect clinical users' judgement and preferences.
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12 hours ago · Bayesian Networks Explained: A probabilistic graphical model using directed acyclic graphs to represent conditional dependencies, assisting in decision-making.
7 hours ago · Explore PyTorch Bayesian methods for effective AI auditing in startups, enhancing model reliability and decision-making.
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16 hours ago · We derive a sufficient condition for the our model to converge in section 3. This theoretical result is general and can apply to a large class of algorithms. In ...
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15 hours ago · PLS SHARE: I'm hiring a PhD student to work on ML theory, to begin in Fall 2025. Topics include: generalization bounds & statistical inference via online ...