Bharat Kaul - RankMe

38 papers A* 6A 5Journal 24Unranked 3

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio
2023	J	`jnl`	AUTOSPARSE: Towards Automated Sparse Training of Deep Neural Networks. CoRR Abhisek Kundu, Naveen K. Mellempudi, Dharma Teja Vooturi, Bharat Kaul, Pradeep Dubey
2022	—	`conf`	Accelerating Deep Learning based Identification of Chromatin Accessibility from noisy ATAC-seq Data. IPDPS Workshops Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul
2021	J	`jnl`	AI Powered Compiler Techniques for DL Code Optimization. CoRR Sanket Tavarageri, Gagandeep Goyal, Sasikanth Avancha, Bharat Kaul, Ramakrishna Upadrasta
2021	J	`jnl`	Efficient and Generic 1D Dilated Convolution Layer for Deep Learning. CoRR Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul
2021	A*	`conf`	GNNerator: A Hardware/Software Framework for Accelerating Graph Neural Networks. DAC Jacob R. Stevens, Dipankar Das, Sasikanth Avancha, Bharat Kaul, Anand Raghunathan
2021	J	`jnl`	GNNerator: A Hardware/Software Framework for Accelerating Graph Neural Networks. CoRR Jacob R. Stevens, Dipankar Das, Sasikanth Avancha, Bharat Kaul, Anand Raghunathan
2021	J	`jnl`	MADRaS : Multi Agent Driving Simulator. J. Artif. Intell. Res. Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, Balaraman Ravindran
2021	J	`jnl`	PolyDL: Polyhedral Optimizations for Creation of High-performance DL Primitives. ACM Trans. Archit. Code Optim. Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Bharat Kaul, Gagandeep Goyal, Ramakrishna Upadrasta
2021	A	`conf`	SEERL: Sample Efficient Ensemble Reinforcement Learning. AAMAS Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul
2020	A*	`conf`	ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract). AAAI Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul
2020	J	`jnl`	MADRaS : Multi Agent Driving Simulator. CoRR Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, Balaraman Ravindran
2020	J	`jnl`	PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives. CoRR Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul
2020	J	`jnl`	PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives. CoRR Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul
2020	J	`jnl`	SEERL: Sample Efficient Ensemble Reinforcement Learning. CoRR Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul
2020	A*	`conf`	SIGMA: A Sparse and Irregular GEMM Accelerator with Flexible Interconnects for DNN Training. HPCA Eric Qin, Ananda Samajdar, Hyoukjun Kwon, Vineet Nadella, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul, Tushar Krishna
2019	J	`jnl`	A Study of BFLOAT16 for Deep Learning Training. CoRR Dhiraj D. Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey
2019	J	`jnl`	Automatic Model Parallelism for Deep Neural Networks with Compiler and Hardware Support. CoRR Sanket Tavarageri, Srinivas Sridharan, Bharat Kaul
2019	J	`jnl`	High Performance Scalable FPGA Accelerator for Deep Neural Networks. CoRR Sudarshan Srinivasan, Pradeep Janedula, Saurabh Dhoble, Sasikanth Avancha, Dipankar Das, Naveen Mellempudi, Bharat Daga, Martin Langhammer, Gregg Baeckler, Bharat Kaul
2019	J	`jnl`	K-TanH: Hardware Efficient Activations For Deep Learning. CoRR Abhisek Kundu, Sudarshan Srinivasan, Eric C. Qin, Dhiraj D. Kalamkar, Naveen K. Mellempudi, Dipankar Das, Kunal Banerjee, Bharat Kaul, Pradeep Dubey
2019	A*	`conf`	Manna: An Accelerator for Memory-Augmented Neural Networks. MICRO Jacob R. Stevens, Ashish Ranjan, Dipankar Das, Bharat Kaul, Anand Raghunathan
2019	J	`jnl`	Mixed Precision Training With 8-bit Floating Point. CoRR Naveen Mellempudi, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul
2019	A*	`conf`	X-MANN: A Crossbar based Architecture for Memory Augmented Neural Networks. DAC Ashish Ranjan, Shubham Jain, Jacob R. Stevens, Dipankar Das, Bharat Kaul, Anand Raghunathan
2018	—	`conf`	Mixed Precision Training of Convolutional Neural Networks using Integer Operations. ICLR (Poster) Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj D. Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesús Corbal, Nikita Shustrov, Roman Dubtsov, Evarist Fomenko, Vadim O. Pirogov
2018	J	`jnl`	Mixed Precision Training of Convolutional Neural Networks using Integer Operations. CoRR Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj D. Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesús Corbal, Nikita Shustrov, Roman Dubtsov, Evarist Fomenko, Vadim O. Pirogov
2018	J	`jnl`	On Scale-out Deep Learning Training for Cloud and HPC. CoRR Srinivas Sridharan, Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Dipankar Das, Mikhail E. Smorkalov, Mikhail Shiryaev, Dheevatsa Mudigere, Naveen Mellempudi, Sasikanth Avancha, Bharat Kaul, Pradeep Dubey
2018	—	`conf`	Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-Out Classifiers. ECCV (8) Apoorv Vyas, Nataraj Jammalamadaka, Xia Zhu, Dipankar Das, Bharat Kaul, Theodore L. Willke
2018	J	`jnl`	Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers. CoRR Apoorv Vyas, Nataraj Jammalamadaka, Xia Zhu, Dipankar Das, Bharat Kaul, Theodore L. Willke
2018	A	`conf`	RAIL: Risk-Averse Imitation Learning. AAMAS Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul
2017	J	`jnl`	Mixed Low-precision Deep Learning Inference using Dynamic Fixed Point. CoRR Naveen Mellempudi, Abhisek Kundu, Dipankar Das, Dheevatsa Mudigere, Bharat Kaul
2017	J	`jnl`	RAIL: Risk-Averse Imitation Learning. CoRR Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul
2017	A*	`conf`	ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks. ISCA Swagath Venkataramani, Ashish Ranjan, Subarno Banerjee, Dipankar Das, Sasikanth Avancha, Ashok Jagannathan, Ajaya Durg, Dheemanth Nagaraj, Bharat Kaul, Pradeep Dubey, Anand Raghunathan
2017	J	`jnl`	Ternary Neural Networks with Fine-Grained Quantization. CoRR Naveen Mellempudi, Abhisek Kundu, Dheevatsa Mudigere, Dipankar Das, Bharat Kaul, Pradeep Dubey
2017	J	`jnl`	Ternary Residual Networks. CoRR Abhisek Kundu, Kunal Banerjee, Naveen Mellempudi, Dheevatsa Mudigere, Dipankar Das, Bharat Kaul, Pradeep Dubey
2016	J	`jnl`	Distributed Deep Learning Using Synchronous Stochastic Gradient Descent. CoRR Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere, Karthikeyan Vaidyanathan, Srinivas Sridharan, Dhiraj D. Kalamkar, Bharat Kaul, Pradeep Dubey
2015	A	`conf`	Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems. IPDPS Dheevatsa Mudigere, Srinivas Sridharan, Anand M. Deshpande, Jongsoo Park, Alexander Heinecke, Mikhail Smelyanskiy, Bharat Kaul, Pradeep Dubey, Dinesh K. Kaushik, David E. Keyes
2014	A	`conf`	Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters. IPDPS Karthikeyan Vaidyanathan, Kiran Pamnany, Dhiraj D. Kalamkar, Alexander Heinecke, Mikhail Smelyanskiy, Jongsoo Park, Daehyun Kim, Aniruddha G. Shet, Bharat Kaul, Bálint Joó, Pradeep Dubey
2012	A	`conf`	High Performance Non-uniform FFT on Modern X86-based Multi-core Systems. IPDPS Dhiraj D. Kalamkar, Joshua D. Trzasko, Srinivas Sridharan, Mikhail Smelyanskiy, Daehyun Kim, Armando Manduca, Yunhong Shu, Matt A. Bernstein, Bharat Kaul, Pradeep Dubey