Part 1:https://omanshuthapliyal.github.io/blog/hrt-conjecture/ Part 2: https://omanshuthapliyal.github.io/blog/hrt-conjecture-part-2/ In the (last couple) (of posts) I explained what the recently …
The code for this project can be found at: https://github.com/omanshuthapliyal/contraction_constrained-safety-head. And the paper can be found at: https://arxiv.org/pdf/2610.02853. A safety classifier …
The code for this project can be found at: https://github.com/omanshuthapliyal/HRM-adapter. And the paper can be found at: https://arxiv.org/pdf/2606.26290. In the previous post, I introduced the …
In the last post I talked about Hankel operators of simple linear dynamical systems. Such operators, and either eigenvalues, “can be used as a proxy for how much memory a task actually requires …
Suppose we are given a linear dynamical system $$G=(A,B,C,D)$$ (recall that a linear system is an input $$x$$ to output $$y$$ map such that $$y_k = Cx_k + Du_k, x_{k+1}=Ax_k+Bu_k$$), and $$G$$ has …
Well, if one were to cut to the chase, it appears to be because of the Central Limit Theorem (CLT). However, there is more underlying structure under the hood as to why the Gaussians seem to be the …
I wrote in a previous post how transformers are kind of like system identification methods applied to some sequence in a state space. In this post we try to understand if the other way round is true. …
Transformer models have captivated a lot of AI research in most of the past decade, and in this post my goal is to make them seem more interesting to controls people, who have much to contribute to …
This blog post summarizes the papers Settling the Reward Hypothesis1 and Utility Theory for Sequential Decision Making 2. The reward hypothesis is at the core of Reinforcement Learning (RL) in that …
Recent news of the SpaceX catching its Starship Super Heavy booster1 is quite discussed and marveled upon in the media, and rightly so. Executing what was done can perhaps be explained as trying to …
Almost always we hear about classification or machine learning problems, the go-to methods to solve the problem are neural networks, or multi-layered percetrons (MLP). Now function approximation …
The internet is filled with machine learning resources, and one of the most annoying things about them is the sheer volume. There are many attempts at making compilations of papers, code, and current …