ইলিয়াস এট আল এর ধারা 3.2। (2019) দেখায় যে শুধুমাত্র প্রতিপক্ষের ত্রুটির উপর একটি মডেলকে প্রশিক্ষণ দিলে মূল পরীক্ষার সেটে…
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A Discussion of ‘Adversarial Examples Are Not Bugs, They Are Features’: Adversarial Examples are Just Bugs, Too
We demonstrate that there exist adversarial examples which are just “bugs”: aberrations in the classifier that are not intrinsic properties…
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A Discussion of ‘Adversarial Examples Are Not Bugs, They Are Features’: Adversarially Robust Neural Style Transfer
A figure in Ilyas, et. al. that struck me as particularly interesting was the following graph showing a correlation between…
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‘প্রতিদ্বন্দ্বী উদাহরণগুলি বাগ নয়, তারা বৈশিষ্ট্যগুলি’ নিয়ে আলোচনা: দরকারী, শক্তিশালী নয়, বৈশিষ্ট্যগুলির দুটি উদাহরণ
‘প্রতিদ্বন্দ্বী উদাহরণগুলি বাগ নয়, তারা বৈশিষ্ট্যগুলি’ নিয়ে আলোচনা: দরকারী, শক্তিশালী নয়, বৈশিষ্ট্যগুলির দুটি উদাহরণ ইলিয়াস প্রমুখ। সংজ্ঞায়িত a বৈশিষ্ট্য একটি…
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Open Questions about Generative Adversarial Networks
By some metrics, research on Generative Adversarial Networks (GANs) has progressed substantially in the past 2 years. Practical improvements to…
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A Visual Exploration of Gaussian Processes
Even if you have spent some time reading about machine learning, chances are that you have never heard of Gaussian…
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Visualizing memorization in RNNs
Memorization in Recurrent Neural Networks (RNNs) continues to pose a challenge in many applications. We’d like RNNs to be able…
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Activation Atlas
Introduction Neural networks can learn to classify images more accurately than any system humans directly design. This raises a natural…
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AI Safety Needs Social Scientists
The goal of long-term artificial intelligence (AI) safety is to ensure that advanced AI systems are reliably aligned with human…
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Distill Update 2018
A little over a year ago, we formally launched Distill as an open-access scientific journal.Distill operated informally for several months…
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