与生
发表于 2025-3-21 20:09:57
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CANON
发表于 2025-3-21 23:10:29
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HERE
发表于 2025-3-22 03:06:03
Evaluation of Human-Understandability of Global Model Explanations Using Decision Treestic and local explanation approaches are deemed interpretable and sufficient in many applications. However, in domains like healthcare, where end users are patients without AI or domain expertise, there is an urgent need for model explanations that are more comprehensible and instil trust in the mo
Merited
发表于 2025-3-22 06:37:11
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Insatiable
发表于 2025-3-22 10:49:08
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justify
发表于 2025-3-22 13:50:37
Towards Explainable Deep Domain Adaptation Transfer learning and, in particular, domain adaptation allows to overcome this issue, by adapting the source model to a new target data distribution and therefore generalizing the knowledge from source to target domain. In this work, we present a method that makes the adaptation process more trans
物质
发表于 2025-3-22 18:52:07
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权宜之计
发表于 2025-3-23 01:12:42
Deep Reinforcement Learning of Autonomous Control Actions to Improve Bus-Service Regularityat buses operating on the same route start to catch up with each other, severely impacting the regularity and the quality of the service. Control actions such as Bus Holding and Stop Skipping can be used to regulate the service and adjust the headway between two buses. Traditionally, this phenomenon
多节
发表于 2025-3-23 03:15:17
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防止
发表于 2025-3-23 09:22:55
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