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Karthik Elamvazhuthi

@clopenloop.bsky.social
51 followers 36 following 80 posts

Hobbyist in control theory and optimal transportation. Gets high on probability densities and the heat equation. hackmd.io/@clopenloop sites.google.com/view/karthikelamva…

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Karthik Elamvazhuthi @clopenloop.bsky.social · 07/10/2026
I am keeping my academic job season cover letter fairly brief this season: “Wrote dissertation before arrival of LLMs. Can also tell jokes.”
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Karthik Elamvazhuthi @clopenloop.bsky.social · 26/09/2026
Blogposts compiled as Some working notes on generative modeling feedback control and Planning. Alternative titles include "Control as Transport" "A Measure Theoretic view of Control" Link: tinyurl.com/35jxd2tt
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Karthik Elamvazhuthi @clopenloop.bsky.social · 09/09/2026
Score matching is known to be related to flow matching in the generative modeling literature. For feedback control applications, a similar connection can be derived using Nelson’s ideas on backward mean derivatives. hackmd.io/xxJpfWCjTRqu...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 03/09/2026
This week in clopenloop we look at the the ergodic control problem. Rather than stabilizing a system to a point, can we make a single trajectory spend the right fraction of time across space? Maybe instead of engineering stability, we want chaos. hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 08/08/2026
For problems like system identification and RL, sampling from the reachable set is important. Many works deal with the discrete time case for sampling. The corresponding sampling strategy for continuous time catastrophically fail: "How not to sample from the reachable set" tinyurl.com/4r6fum2m
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Karthik Elamvazhuthi @clopenloop.bsky.social · 12/07/2026
The proximal point scheme can be seen as a MPC like iteration for the single integrator. So naturally, there should be a similar optimal control scheme for the heavy ball dynamics using the double integrator. Blog post: hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 03/07/2026
The sub-Laplacian encodes information about a control system's geometry. One can use linear Poisson equation to design controllers for nonlinear control systems. An interesting connection between linear PDE tools and geometric control. Link to post: hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 22/06/2026
It is standard to view control of multi-agent systems or swarms are special cases of classical control problems. But in the measure viewpoint, classical control problems are special cases of the swarm problem. Latest post: hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 07/06/2026
Blogpost on how the maximum principle of optimal control and the corresponding Hamiltonian system can be integrated with flow matching to develop a regression based approach to control synthesis, and a comparison with an elementary model based policy gradient method. hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 24/05/2026
Offered to present a tutorial on diffusion models for control, at L4DC26. Got rejected on grounds I didn’t have enough coorganizers. Somehow I must recruit followers of an idea before I can share the idea.
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Karthik Elamvazhuthi @clopenloop.bsky.social · 22/05/2026
Continuing with the line thinking that topological obstructions to smooth stabilization can be avoided by adding noise. All a simple consequence of an eerie observation of Khasʹminskiĭ's that global recurrence plus local stability gives asymptotic stability. Preprint: tinyurl.com/mth23ux4
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Karthik Elamvazhuthi @clopenloop.bsky.social · 20/05/2026
One does not need white noise to implement the principle of denoising diffusion. For instance, RRT* from robotics is a more efficient way to explore the space than Brownian motion. One can combine this with flow matching to denoise the system to construct feedback navigating control laws.
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Karthik Elamvazhuthi @clopenloop.bsky.social · 18/05/2026
If one starts with a reference ergodic process, and composes it with a transport map, then you get a new process ergodic with respect to the terminal transported measure.
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Reposted by Karthik Elamvazhuthi
International Federation of Automatic Control @ifac-control.bsky.social · 15/05/2026
🥇 Congrats to Arthur J. Krener — winner of the IFAC Giorgio Quazza Medal 2023–2026! For fundamental contributions to nonlinear systems analysis, estimation, control & optimization. 50+ years shaping the field. To be honored at #IFAC2026 in Busan. 📄 buff.ly/E6AmEAn
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Karthik Elamvazhuthi @clopenloop.bsky.social · 14/05/2026
Started the day bickering with my partner if the swallows around the house are demonstrating milling behavior or just high in entropy. #meanfieldwife
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Karthik Elamvazhuthi @clopenloop.bsky.social · 08/05/2026
Two waves in the control community 2010s: "Multi-agent systems need control!" 2020s: "ML needs control!" Both Times: So anyway, we have, dx/dt = Ax + Bu...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 06/05/2026
Hooked up a hand gesture system with a swarm of interaction particles, leading to a notion of “Swarm bending” Motivates interesting theoretical questions regarding which swarm models are “bendable.” hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 06/05/2026
Bahaha Source: michaellevitin.net/Book/TSG2305...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 05/05/2026
I get more citations from roboticists and applied mathematicians, than control theorists in my area of research. I call this the bull curve.
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Karthik Elamvazhuthi @clopenloop.bsky.social · 04/05/2026
Forget proofs. I want to learn to make falling cats like these. Source: Lecture notes on sub-Riemannian geometry from the Lie group viewpoint - Enrico Le Donne cvgmt.sns.it/media/doc/pa...
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Reposted by Karthik Elamvazhuthi
Poetry Daily @poetrydaily.bsky.social · 27/04/2026
Today's Feature: Our Readers on Poems from Poetry Daily including "Bounded Regret Algorithim" by Zoë Hitzig from Not Us Now published by Changes Press Read here: poems.com/poem/bounded...
poems.com
Bounded Regret Algorithm
I know with certainty almost nothing. Yet here I am executing legions of decisions each moment.
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Karthik Elamvazhuthi @clopenloop.bsky.social · 21/04/2026
In today's post, bees go down a controlled gradient flow to find their homes. 🐝🏠 hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 16/04/2026
Round 2 of collective decision making as a feedback control problem. This time we visit the Seeley model. How do bees avoid deadlock and obstructions to stabilization? To control engineers need to practice headbutting? hackmd.io/yTBuClZ0Sh65...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 08/04/2026
Latest blog post of clopenloop is coincidentally on how the generative modeling method of flow matching can be used to go from open loop trajectories to closed loop based feedback synthesis. t.co/q0InluvTWy
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Karthik Elamvazhuthi @clopenloop.bsky.social · 29/03/2026
The inverted pendulum is steered to its Sisyphean headstand once more. But without eigenvalues, Lyapunov, or bribery. Instead, using denoising as a control steering mechanism. Latest post on generative modeling for control: hackmd.io/kjV3PiI4ROOP...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 28/03/2026
The Fall from the Ivory Tree An essay on the despair of the academic job cycle, and the hope that must follow - hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 14/02/2026
Link to my zoom talk at the GERAD Research Center, "A Transport Theoretic Perspective for Nonlinear Control": www.youtube.com/watch?v=cXy1... Thanks to the organizers, Aditya Mahajan, Peter Caines, and Shuang Gao for the wonderful opportunity to present and great interactions.
youtube.com
A Transport Theoretic Perspective for Nonlinear Control, Karthik Elamvazhuthi
YouTube video by GERAD Recherche
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Karthik Elamvazhuthi @clopenloop.bsky.social · 09/02/2026
The generative modeling for control lectures are proceeding in nonlinear order. Here is one on a control generalization of gradient descent that I refer to as nonholonomic gradient descent. I explain why it's doomed to fail due to Brockett, and how noise might save us. hackmd.io/pTtk6ohHSBSf...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 03/02/2026
Encoding geometry in neural network architectures has wide applications, from robots' configuration spaces to safety. We present natural ways to enforce constraints by design. Link to preprint: www.researchgate.net/publication/... #geometricdeeplearning
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Karthik Elamvazhuthi @clopenloop.bsky.social · 08/01/2026
All hail the Lie bracket 🙌
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Karthik Elamvazhuthi @clopenloop.bsky.social · 24/11/2025
I’m writing notes on how generative modeling connects with control theory. Starting with intuition: simulations, nonlinear control, and how stochastic dynamics can shape long-term behavior. LN1 (Fokker–Planck): hackmd.io/@clopenloop/... LN2 (Nonholonomic Fokker-Planck): hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 31/10/2025
The road to the maximum principle turns out to be more non-smooth than one might expect. Boltyanski, Martini & Soltan’s book ( Geometric Methods and Optimization Problems) has far more drama than you’d guess from the Sussmann–Willems survey.
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Karthik Elamvazhuthi @clopenloop.bsky.social · 24/10/2025
Job season in academia can take a toll on confidence, identity, and energy. You’re not alone. Sometimes it helps to zoom out. Hunter Wapman’s thesis highlights some interesting hiring patterns: www.hne.golf/static/pdfs/... Non-US trends may differ, perhaps shaping distinct knowledge bubbles.
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Karthik Elamvazhuthi @clopenloop.bsky.social · 17/10/2025
Multi-agent control often feels like control theorists doing dynamical systems instead of control theory. What if we posed it like classic control problems. Collective decision-making as feedback stabilizability. Turns out, it leads to a strange kind of control problem. hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 11/10/2025
Wowza! arxiv.org/html/2510.07...
arxiv.org
Nested superposition principle for random measures and the geometry of the Wasserstein on Wasserstein space
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Karthik Elamvazhuthi @clopenloop.bsky.social · 08/10/2025
A basin of attraction
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Karthik Elamvazhuthi @clopenloop.bsky.social · 24/09/2025
An interesting result on how LQ problems in optimal control can fail to have minimizers: arxiv.org/pdf/1311.200... (in an almost merciless way).
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Karthik Elamvazhuthi @clopenloop.bsky.social · 21/09/2025
Optimal Transport (OT) is emerging as a versatile tool for control questions. We show an OT-based way to sample from the reachable set (RS), especially useful when systems have strong attractors. www.researchgate.net/publication/... RS of Van der Pol vs. naive random sampling (below).
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Karthik Elamvazhuthi @clopenloop.bsky.social · 19/07/2025
Finally, my YouTube debut! A recording of my talk at the AI and data seminar series organized by the Automatic Control Engineering Network. m.youtube.com/watch?v=o-4B... Here I pontificate on using time reversals of diffusions for stabilization and planning problems.
m.youtube.com
ACE AI and Data Talk Series-Dr. Karthik Elamvazhuthi
YouTube video by Automatic Control Engineering Network (ACE)
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Karthik Elamvazhuthi @clopenloop.bsky.social · 30/06/2025
I am starting to compile some notes on Generative Modeling for Control Theory. The goal is to include topics such as degenerate Fokker-Planck equations (FPEs) and Optimal transport theory. Here is a first post on the classical (nicer) FPE and its long-term behavior. hackmd.io/@clopenloop/...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 05/06/2025
Probably a good chapter if it starts with Nietzsche. - Tanja Eisner, Bálint Farkas, Markus Haase and Rainer Nagel (Operator Theoretic Aspects of Ergodic Theory)
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Karthik Elamvazhuthi @clopenloop.bsky.social · 30/05/2025
Permutation equivariance is a common property of multi-agent systems. In a new paper with Shiba Biswal and @rishisonthalia.bsky.social ‬, accepted to ICML, we leverage this property shared by transformers, for mean field models of collective behavior. #machinelearning arxiv.org/abs/2410.16295
arxiv.org
Universal Approximation of Mean-Field Models via Transformers
This paper investigates the use of transformers to approximate the mean-field dynamics of interacting particle systems exhibiting collective behavior. Such systems are fundamental in modeling phenomen...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 29/05/2025
Nice set of notes connecting the finite particle matching problem to the continuum optimal transport solution. arxiv.org/abs/2505.10175
arxiv.org
From Combinatorics to Partial Differential Equations
The optimal matching of point clouds in $\mathbb{R}^d$ is a combinatorial problem; applications in statistics motivate to consider random point clouds, like the Poisson point process. There is a cruci...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 21/05/2025
It’s known that the Laplacian operator, describing how heat flows through a domain, carries rich information about the domain’s underlying geometry. Similarly, one can understand the geometry of a control system using its sub-Laplacian. See comptes-rendus.academie-sciences.fr/mathematique...
comptes-rendus.academie-sciences.fr
A linear test for global nonlinear controllability
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Reposted by Karthik Elamvazhuthi
incontrolpodcast.bsky.social @incontrolpodcast.bsky.social · 16/05/2025
🎙️ New episode! Anders Rantzer (@lunduniversity) walks us through robust control, IQCs, the KYP lemma, nonlinear and hybrid systems, scalability and positivity, and dual (adaptive) control. A journey shaped by the dialogue between Western and Russian control traditions — don’t miss it! 🧠🚀
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Karthik Elamvazhuthi @clopenloop.bsky.social · 25/04/2025
Nice survey on the how optimal control needed some genuine innovations over classical calculus of variation, and how non-smooth tools apply in this setting. No mention of needle variations, unfortunately. link.springer.com/article/10.1...
link.springer.com
Optimal Trajectories and the Neoclassical Calculus of Variations - Set-Valued and Variational Analysis
The calculus of variations, a venerable subject connected for centuries with physics, was largely superseded in the 1960s by the theory of optimal control that arose then from modern engineering. Math...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 20/04/2025
If we are not careful, all our jobs will be replaced by conditional probability distributions.
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Karthik Elamvazhuthi @clopenloop.bsky.social · 14/04/2025
Denoising an unstable double integrator to sum of two Dirac measures. See details on the theory in the preprint: www.researchgate.net/publication/... #controltheory #machinelearning #diffusionmodels bsky.app/profile/clop...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 06/04/2025
A blog post on how diffusion models can be used for planning in domains with obstacles : hackmd.io/@TAzH1D5uSQO...
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Karthik Elamvazhuthi @clopenloop.bsky.social · 26/03/2025
When it comes to optimal transport, think Eulerian and compute Lagrangian. In a new paper, we present a numerical method embracing this philosophy, with potential applications to controlling swarms and sampling. www.esaim-cocv.org/articles/coc...
esaim-cocv.org
A blob method for mean field control with terminal constraints | ESAIM: Control, Optimisation and Calculus of Variations (ESAIM: COCV)Mendeley
ESAIM: Control, Optimisation and Calculus of Variations (ESAIM: COCV) publishes rapidly and efficiently papers and surveys in the areas of control, optimisation and calculus of variations
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