Abstract: Quantized neural networks significantly reduce storage requirements and computational complexity by lowering the numerical precision of weights and activations. Among these, binary neural ...
ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...
Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Abstract: Early identification and management of Diabetic Foot Ulcers (DFU) are critical for preventing severe complications, particularly in the Indian subcontinent where DFU prevalence is high. This ...
Binary cross-entropy (BCE) is the default loss function for binary classification—but it breaks down badly on imbalanced datasets. The reason is subtle but important: BCE weighs mistakes from both ...
Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!
At the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025) in Suzhou, China this week (November 4-9, 2025), researchers from Bloomberg’s AI Engineering group and its BLAW ...
1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
Thank you for the awesome library. I am trying to determine whether a specific task would be a good fit for distillation. I am working on training a distilled binary classification model to determine ...
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