Популярное

Музыка Кино и Анимация Автомобили Животные Спорт Путешествия Игры Юмор

Интересные видео

2025 Сериалы Трейлеры Новости Как сделать Видеоуроки Diy своими руками

Топ запросов

смотреть а4 schoolboy runaway турецкий сериал смотреть мультфильмы эдисон
dTub
Скачать

Learning Causal World Models from Acting and Seeing Using Score Functions by Karthikeyan Shanmugam

Автор: International Centre for Theoretical Sciences

Загружено: 2025-09-30

Просмотров: 176

Описание:

Program - Data Science: Probabilistic and Optimization Methods II

ORGANIZERS: Jatin Batra (TIFR, Mumbai, India), Vivek Borkar (IIT Bombay, India), Sandeep Juneja (Ashoka University, Haryana, India), Praneeth Netrapalli (Google DeepMind, India) and Devavrat Shah (MIT, Cambridge, USA)

DATE & TIME: 04 August 2025 to 15 August 2025

VENUE: Chandrasekhar Auditorium, ICTS Bengaluru


Probability and Optimization are two of the core areas that underpin much of data science and machine learning. The current workshop, Data Science: Probabilistic and Optimization Methods, will focus on this field with a special focus on shedding light on the core principles that enable both current successes and future breakthroughs in data science and machine learning. The program begins with a bootcamp covering foundational topics in probability, statistics, and optimization, followed by tutorials and research talks highlighting innovative ideas and open challenges. The topics covered will include new theoretical developments in some of the areas likely to be key in upcoming data science research such as reinforcement learning, generative modelling, causal inference and advanced probability and optimization. Through these sessions, participants will see how rigorous theory can inform robust, adaptable systems—and have opportunities to propose fresh lines of inquiry.

A centerpiece of the event is the Infosys-ICTS Turing lectures, delivered by Andrea Montanari (Stanford University), whose work spans several areas including probability, statistical physics, statistics, theoretical computer science, information theory and machine learning. We warmly invite researchers, students, and practitioners from all backgrounds to join this collaborative exploration of data science’s evolving theoretical landscape—and help shape its next wave of discoveries.

Organized with support from Google, Microsoft Research India and Safexpress Centre for Data, Learning and Decision Sciences at Ashoka University.

CONTACT US: [email protected]
PROGRAM LINK: https://www.icts.res.in/program/dspom

Learning Causal World Models from Acting and Seeing Using Score Functions by Karthikeyan Shanmugam

Поделиться в:

Доступные форматы для скачивания:

Скачать видео mp4

  • Информация по загрузке:

Скачать аудио mp3

Похожие видео

array(0) { }

© 2025 dtub. Все права защищены.



  • Контакты
  • О нас
  • Политика конфиденциальности



Контакты для правообладателей: [email protected]