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Explore cutting-edge cosmological research through hands-on projects and expert insights. Develop skills in analyzing large-scale structure surveys and multi-messenger cosmology data.
Explore cutting-edge cosmological research through hands-on projects and expert insights. Gain valuable skills for analyzing large-scale structure surveys and cosmic microwave background data.
Explore lunar mineral mapping and volatiles at the poles in this talk on gravitational-wave detection missions, discussing technological advancements and scientific opportunities for breakthrough observations.
Explore radar observations of lunar poles, discussing techniques, findings, and implications for future lunar missions and scientific understanding of Earth's celestial neighbor.
Explore lunar pole topography using Chandrayaan-2 cameras to create digital elevation models, advancing our understanding of the Moon's polar regions.
Explore India's lunar missions, their scientific objectives, and future plans. Gain insights into the country's space exploration efforts and contributions to lunar research.
Explores lunar gravitational-wave detection concepts, technologies, and scientific opportunities in the decihertz band, discussing mission planning and potential breakthroughs in multi-messenger astronomy.
Explore challenges and prospects of low-level end-to-end reconstruction using machine learning in high-energy physics, focusing on innovative techniques and future applications.
Explore Boosted Decision Trees and Neural Networks for particle classification in High Energy Physics, enhancing data analysis techniques for groundbreaking discoveries.
Introduction to Boosted Decision Trees and Neural Networks for particle classification in High Energy Physics, covering fundamental concepts and applications in experimental data analysis.
Explore advanced machine learning techniques for high energy physics, including Deepsets, Graph Neural Networks, and Transformers, to analyze complex particle physics data.
Explore differentiable programming for optimizing experiments in high-energy physics, focusing on end-to-end solutions and advanced machine learning techniques.
Explore data-driven approaches in cosmology, leveraging statistical methods and machine learning to analyze vast datasets and uncover insights about the universe's structure and evolution.
Explore advanced neural simulation-based inference techniques for high energy physics, focusing on applications in data analysis and new physics discovery at particle colliders.
Explore neural simulation-based inference techniques for high energy physics, focusing on advanced machine learning applications in data analysis and new physics discovery.
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