no code implementations • 11 Nov 2022 • Jerry Luo, Cosmin Paduraru, Octavian Voicu, Yuri Chervonyi, Scott Munns, Jerry Li, Crystal Qian, Praneet Dutta, Jared Quincy Davis, Ningjia Wu, Xingwei Yang, Chu-Ming Chang, Ted Li, Rob Rose, Mingyan Fan, Hootan Nakhost, Tinglin Liu, Brian Kirkman, Frank Altamura, Lee Cline, Patrick Tonker, Joel Gouker, Dave Uden, Warren Buddy Bryan, Jason Law, Deeni Fatiha, Neil Satra, Juliet Rothenberg, Mandeep Waraich, Molly Carlin, Satish Tallapaka, Sims Witherspoon, David Parish, Peter Dolan, Chenyu Zhao, Daniel J. Mankowitz
This paper is a technical overview of DeepMind and Google's recent work on reinforcement learning for controlling commercial cooling systems.
no code implementations • 16 Sep 2022 • William Wong, Praneet Dutta, Octavian Voicu, Yuri Chervonyi, Cosmin Paduraru, Jerry Luo
Reinforcement learning (RL) techniques have been developed to optimize industrial cooling systems, offering substantial energy savings compared to traditional heuristic policies.
Hierarchical Reinforcement Learning reinforcement-learning +1
no code implementations • 26 Jul 2022 • Yuri Chervonyi, Praneet Dutta, Piotr Trochim, Octavian Voicu, Cosmin Paduraru, Crystal Qian, Emre Karagozler, Jared Quincy Davis, Richard Chippendale, Gautam Bajaj, Sims Witherspoon, Jerry Luo
We present a hybrid industrial cooling system model that embeds analytical solutions within a multi-physics simulation.
no code implementations • 7 Nov 2021 • Matthew Mithra Noel, Shubham Bharadwaj, Venkataraman Muthiah-Nakarajan, Praneet Dutta, Geraldine Bessie Amali
The recent discovery of special human neocortical pyramidal neurons that can individually learn the XOR function highlights the significant performance gap between biological and artificial neurons.
no code implementations • 30 Aug 2021 • Mathew Mithra Noel, Arunkumar L, Advait Trivedi, Praneet Dutta
This ability to learn complex high-dimensional functions hierarchically can be attributed to the use of nonlinear activation functions.
1 code implementation • 18 Nov 2020 • Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adria Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Perolat, Bart De Vylder, Ali Eslami, Mark Rowland, Andrew Jaegle, Remi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis
The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individual sports, including baseball, basketball, and tennis.
no code implementations • 16 Nov 2019 • Praneet Dutta, Bruce Power, Adam Halpert, Carlos Ezequiel, Aravind Subramanian, Chanchal Chatterjee, Sindhu Hari, Kenton Prindle, Vishal Vaddina, Andrew Leach, Raj Domala, Laura Bandura, Massimo Mascaro
We propose GAN-based image enhancement models for frequency enhancement of 2D and 3D seismic images.
no code implementations • 7 Sep 2019 • Praneet Dutta, Joe Cheuk, Jonathan S Kim, Massimo Mascaro
We see that our model is able to perform much better than random exploration, being more regret efficient and able to converge with a limited number of samples, while remaining very general and easy to use due to the meta-learning approach.