Investigation of certain topics of machine learning techniques and discussion of their motivation, design, and applications.
Machine Learning Techniques
- Inverse Design of Amorphous Materials, and the Relaxation Problem
- From Soft Guidance to Hard Constraints on Diffusion Sampling
- Diffusion Models in Discrete Space
- On the Horizon of Large Trajectory Models
- Generating Spatiotemporal Trajectories
- Self-supervised Learning of Trajectories
- End-to-end Learning of Trajectories
- Introduction to Deep Learning for Trajectories
- Encoding Relative Positions with RoPE
- New Generations of BERT