On the Use of Pseudorandom Sequences for High Speed Resource Allocators in Superscalar Processors. - Srivatsan Srinivasan; Lizy Kurian John (ICCD, 1999)

Formal Verification of a Snoop-Based Cache Coherence Protocol Using Symbolic Model Checking. - Srivatsan Srinivasan; Parminder Singh Chhabra; Praveen Kumar Jaini; Adnan Aziz; Lizy Kurian John (VLSI Design, 1999)

Evaluating Reinforcement Learning Algorithms in Observational Health Settings. - Omer Gottesman; Fredrik D. Johansson; Joshua Meier; Jack Dent; Donghun Lee; Srivatsan Srinivasan; Linying Zhang; Yi Ding; David Wihl; Xuefeng Peng; Jiayu Yao; Isaac Lage; et al. (CoRR, 2018)

Introducing the New Student Activities Committee. - Srivatsan Srinivasan (IEEE Robotics Autom. Mag., 2018)

Raising Awareness for Robotics-Aided Ocean Conservation [Student Corner]. - Srivatsan Srinivasan (IEEE Robotics Autom. Mag., 2018)

Truly Batch Apprenticeship Learning with Deep Successor Features. - Donghun Lee; Srivatsan Srinivasan; Finale Doshi-Velez (IJCAI, 2019)

Output-Constrained Bayesian Neural Networks. - Wanqian Yang; Lars Lorch; Moritz A. Graule; Srivatsan Srinivasan; Anirudh Suresh; Jiayu Yao; Melanie F. Pradier; Finale Doshi-Velez (CoRR, 2019)

Misty-A Development Platform for Socially Assistive Robots [Student's Corner]. - Srivatsan Srinivasan (IEEE Robotics Autom. Mag., 2019)

The DeepMind Chinese-English Document Translation System at WMT2020. - Lei Yu 008; Laurent Sartran; Po-Sen Huang; Wojciech Stokowiec; Domenic Donato; Srivatsan Srinivasan; Alek Andreev; Wang Ling; Sona Mokrá; Agustin Dal Lago; Yotam Doron; Susannah Young; et al. (WMT@EMNLP, 2020)

Wearable Assistive Devices for the Visually Challenged [Student's Corner]. - Srivatsan Srinivasan (IEEE Robotics Autom. Mag., 2020)

Better Chinese Sentence Segmentation with Reinforcement Learning. - Srivatsan Srinivasan; Chris Dyer (ACL/IJCNLP (Findings), 2021)

An empirical study of implicit regularization in deep offline RL. - Çaglar Gülçehre; Srivatsan Srinivasan; Jakub Sygnowski; Georg Ostrovski; Mehrdad Farajtabar; Matthew Hoffman 002; Razvan Pascanu; Arnaud Doucet (Trans. Mach. Learn. Res., 2022)

Placement Optimization for NoC-Enhanced FPGAs. - Srivatsan Srinivasan; Andrew Boutros; Fatemehsadat Mahmoudi; Vaughn Betz (FCCM, 2023)

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. - Michaël Mathieu; Sherjil Ozair; Srivatsan Srinivasan; Çaglar Gülçehre; Shangtong Zhang; Ray Jiang; Tom Le Paine; Richard Powell; Konrad Zolna; Julian Schrittwieser; David H. Choi; Petko Georgiev; et al. (CoRR, 2023)

Reinforced Self-Training (ReST) for Language Modeling. - Çaglar Gülçehre; Tom Le Paine; Srivatsan Srinivasan; Ksenia Konyushkova; Lotte Weerts; Abhishek Sharma 015; Aditya Siddhant; Alex Ahern; Miaosen Wang; Chenjie Gu; Wolfgang Macherey; Arnaud Doucet; et al. (CoRR, 2023)

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. - Soham De; Samuel L. Smith; Anushan Fernando; Aleksandar Botev; George-Cristian Muraru; Albert Gu; Ruba Haroun; Leonard Berrada; Yutian Chen 001; Srivatsan Srinivasan; Guillaume Desjardins; Arnaud Doucet; et al. (CoRR, 2024)

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. - Aleksandar Botev; Soham De; Samuel L. Smith; Anushan Fernando; George-Cristian Muraru; Ruba Haroun; Leonard Berrada; Razvan Pascanu; Pier Giuseppe Sessa; Robert Dadashi; Léonard Hussenot; Johan Ferret; et al. (CoRR, 2024)

Imagen 3. - Jason Baldridge; Jakob Bauer; Mukul Bhutani; Nicole Brichtova; Andrew Bunner; Kelvin Chan; Yichang Chen; Sander Dieleman; Yuqing Du; Zach Eaton-Rosen; Hongliang Fei; Nando de Freitas; et al. (CoRR, 2024)