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title
eXplainable AI approaches for debugging and diagnosis.
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Workshop @ NeurIPS2021 14 December
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eXplainable AI approaches for debugging and diagnosis.
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2026-03-04 22:53:56
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eXplainable AI approaches for debugging and diagnosis. | Workshop @ NeurIPS2021 14 December Skip to the content. eXplainable AI approaches for debugging and diagnosis. Workshop @ NeurIPS2021 | 14 December About Schedule FAQ Slack CFP Organization Contacts About Recently, artificial intelligence has seen the explosion of deep learning models, which are able to reach super-human performance in several tasks, finding application in many domains. These performance improvements, however, come at a cost: DL models are uninterpretable black boxes, where one feeds an input and obtains an output without understanding the motivations behind that prediction or decision. To address this problem, two research areas are particularly active: the eXplainable AI (XAI) field and the visual analytics community. The eXplainable XAI field tries to address such problems by proposing algorithmic methods that can explain, at least partially, the behavior of these networks. Their work...
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