Eksplorasi makalah akademik, arsitektur sistem, dan implementasi kode.
# Stop Guessing Your Batch Size: Mastering the Gradient Noise Scale (GNS) Choosing the "right" batch size is often treated as a dark art in deep lear...
# Demystifying the Neural Tangent Kernel (NTK): When Neural Networks Become Linear Training a deep neural network often feels like alchemy. We naviga...
# Beyond Overfitting: Understanding "Grokking" in Neural Networks Have you ever trained a model only to find that it perfectly memorized the training...
# Beyond the Bottom: Improving Generalization with Sharpness-Aware Minimization (SAM) In the quest for the perfect deep learning model, we are taught...
# Decoding the Black Box: Understanding Neural Network Similarity with CKA Have you ever wondered if two different neural networks, trained on the sa...
# Beyond the Overfitting Myth: Understanding Implicit Regularization in Deep Learning **Why does making a neural network larger often make it perform...
# Stop Over-Parameterizing: Understanding Chinchilla Scaling Laws In the early days of the LLM gold rush, the prevailing wisdom was simple: **Bigger...
# Beyond Addition: Mastering Rotary Position Embeddings (RoPE) in RoFormer In the evolution of Transformer architectures, how a model perceives the o...
# Finding Balance: Zero-Sum Perfect Matchings in Complete Graphs In the realm of extremal graph theory, we often ask: *What structural properties mus...