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Explore the intersection of reinforcement learning, GANs, and imitation learning in this short, focused study by Yannic Kilcher. Learn to achieve specific goals while adhering to a dataset of demonstrations.
Explore implicit differentiation in machine learning with Yannic Kilcher's short program. Learn to optimize inner loops, understand meta-learning, and apply a unified framework.
Explore the path to Artificial General Intelligence (AGI) through reward maximization in this short, engaging study by Yannic Kilcher. Delve into philosophy, engineering, and futurism.
Explore reinforcement learning in shifting environments with Yannic Kilcher's under 1-hour study of Recurrent Independent Mechanisms. Gain insights into fast and slow learning procedures for superior results and stability.
Explore Facebook AI's Expire-Span, a Transformer XL variant that assigns expiration dates to signals, managing memory and compute requirements. Offered by Yannic Kilcher.
Explore FNet architecture and Fourier Transforms in this brief, insightful study by Yannic Kilcher. Learn how to speed up Transformer encoders and reduce compute requirements.
Explore how DDPMs can outperform GANs in image generation with Yannic Kilcher's under 1-hour study of a machine learning research paper.
Explore the principles of convolution and involution in computer vision with Yannic Kilcher. Learn about spatial-specific computations, the Involution Operator, and RedNet architecture in under an hour.
Explore MLP-Mixer architecture, its experimental results, and effects of scale in less than an hour with Yannic Kilcher. Dive into the future of computer vision beyond CNNs and Transformers.
Explore Facebook AI's DINO system, combining Self-Supervised Learning and Vision Transformer architecture for impressive results in computer vision. Offered by Yannic Kilcher, under 1 hour.
Explore the concept of Neural Radiance Fields (NeRF) and view synthesis with Yannic Kilcher in less than an hour. Learn about training NeRF from sparse views, volume rendering, and more.
Explore machine learning with Yannic Kilcher in less than an hour. Learn about DreamCoder, a system that solves problems by writing programs, and its potential in deep learning.
Explore DeepMind's Perceiver model with Yannic Kilcher in under an hour. Understand its architecture, built-in assumptions, and how it solves the quadratic bottleneck problem.
Explore the potential of pretrained transformers in machine learning across different modalities with Yannic Kilcher. Learn about fine-tuning, modality transfer, and network architecture in under an hour.
Explore the future of AI with Yannic Kilcher's deep dive into Self-Supervised Learning (SSL), discussing its potential to reduce label dependency and enhance knowledge transfer in under an hour.
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