<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine Learning on Omanshu Thapliyal</title><link>https://omanshuthapliyal.github.io/keywords/machine-learning/</link><description>Recent content in Machine Learning on Omanshu Thapliyal</description><generator>Hugo</generator><language>en</language><lastBuildDate>Wed, 12 Aug 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://omanshuthapliyal.github.io/keywords/machine-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>Bounded Reachability &amp; Jailbreak Detection via Contraction-Constrained State Space Models</title><link>https://omanshuthapliyal.github.io/papers/bounded-reachability-jailbreak-detection-via-contraction-constrained-state-space-models/</link><pubDate>Wed, 12 Aug 2026 00:00:00 +0000</pubDate><guid>https://omanshuthapliyal.github.io/papers/bounded-reachability-jailbreak-detection-via-contraction-constrained-state-space-models/</guid><description/></item><item><title>SSM Adapters via Hankel Reduced-order Modeling: Injection Site Determines Task Suitability in Long-Context Fine-Tuning</title><link>https://omanshuthapliyal.github.io/papers/ssm-adapters-via-hankel-reduced-order-modeling-injection-site-determines-task-suitability-in-long-context-fine-tuning/</link><pubDate>Fri, 10 Jul 2026 00:00:00 +0000</pubDate><guid>https://omanshuthapliyal.github.io/papers/ssm-adapters-via-hankel-reduced-order-modeling-injection-site-determines-task-suitability-in-long-context-fine-tuning/</guid><description/></item><item><title>A Multi-Head Attention Approach for SLA Compliance Monitoring in Data Centers</title><link>https://omanshuthapliyal.github.io/papers/a-multi-head-attention-approach-for-sla-compliance-monitoring-in-data-centers/</link><pubDate>Wed, 06 May 2026 00:00:00 +0000</pubDate><guid>https://omanshuthapliyal.github.io/papers/a-multi-head-attention-approach-for-sla-compliance-monitoring-in-data-centers/</guid><description/></item><item><title>Safe Navigation using Neural Radiance Fields via Reachable Sets</title><link>https://omanshuthapliyal.github.io/papers/safe-navigation-using-neural-radiance-fields-via-reachable-sets/</link><pubDate>Fri, 20 Mar 2026 00:00:00 +0000</pubDate><guid>https://omanshuthapliyal.github.io/papers/safe-navigation-using-neural-radiance-fields-via-reachable-sets/</guid><description/></item><item><title>Embedding Safety Requirements into Learning-Based Controllers for Urban Air Mobility Applications</title><link>https://omanshuthapliyal.github.io/papers/embedding-safety-requirements-into-learning-based-controllers-for-urban-air-mobility-applications/</link><pubDate>Thu, 04 Jan 2024 00:00:00 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Control</title><link>https://omanshuthapliyal.github.io/papers/approximating-reachable-sets-for-neural-network-based-models-in-real-time-via-optimal-control/</link><pubDate>Sat, 01 Jul 2023 00:00:00 +0000</pubDate><guid>https://omanshuthapliyal.github.io/papers/approximating-reachable-sets-for-neural-network-based-models-in-real-time-via-optimal-control/</guid><description/></item><item><title>Data-driven Cyberattack Synthesis against Network Control Systems</title><link>https://omanshuthapliyal.github.io/papers/data-driven-cyberattack-synthesis-against-network-control-systems/</link><pubDate>Sun, 01 Jan 2023 00:00:00 +0000</pubDate><guid>https://omanshuthapliyal.github.io/papers/data-driven-cyberattack-synthesis-against-network-control-systems/</guid><description/></item><item><title>Provably Stabilizing Model-Free Q-Learning for Unknown Bilinear Systems</title><link>https://omanshuthapliyal.github.io/papers/provably-stabilizing-model-free-q-learning-for-unknown-bilinear-systems/</link><pubDate>Mon, 29 Aug 2022 00:00:00 +0000</pubDate><guid>https://omanshuthapliyal.github.io/papers/provably-stabilizing-model-free-q-learning-for-unknown-bilinear-systems/</guid><description/></item><item><title>Learning Based Cyberattack Design and Defense for Supervisory Control Systems</title><link>https://omanshuthapliyal.github.io/papers/learning-based-cyberattack-design-and-defense-for-supervisory-control-systems/</link><pubDate>Fri, 25 Jun 2021 00:00:00 +0000</pubDate><guid>https://omanshuthapliyal.github.io/papers/learning-based-cyberattack-design-and-defense-for-supervisory-control-systems/</guid><description/></item></channel></rss>