Aditya Ramesh

According to our database, Aditya Ramesh authored at least 31 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2023

Being Trustworthy is Not Enough: How Untrustworthy Artificial Intelligence (AI) Can Deceive the End-Users and Gain Their Trust.

Nikola Banovic, Zhuoran Yang, Aditya Ramesh, Alice Liu

Proc. ACM Hum. Comput. Interact., April, 2023

Mindstorms in Natural Language-Based Societies of Mind.

Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piekos, Aditya Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanic, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber

CoRR, 2023

The Benefits of Model-Based Generalization in Reinforcement Learning.

Kenny John Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber

Proceedings of the International Conference on Machine Learning, 2023

Goal-Conditioned Generators of Deep Policies.

Francesco Faccio, Vincent Herrmann, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Flexible Machine Learning Algorithms for Clinical Gait Assessment Tools.

Christian Greve, Hobey Tam, Manfred G. Grabherr, Aditya Ramesh, Bart Scheerder, Juha M. Hijmans

Sensors, 2022

Recurrent Neural-Linear Posterior Sampling for Nonstationary Contextual Bandits.

Aditya Ramesh, Paulo E. Rauber, Michelangelo Conserva, Jürgen Schmidhuber

Neural Comput., 2022

General Policy Evaluation and Improvement by Learning to Identify Few But Crucial States.

Francesco Faccio, Aditya Ramesh, Vincent Herrmann, Jean Harb, Jürgen Schmidhuber

CoRR, 2022

Hierarchical Text-Conditional Image Generation with CLIP Latents.

Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen

CoRR, 2022

Exploring through Random Curiosity with General Value Functions.

Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen

Proceedings of the International Conference on Machine Learning, 2022

2021

Unsupervised Neural Machine Translation with Generative Language Models Only.

Jesse Michael Han, Igor Babuschkin, Harrison Edwards, Arvind Neelakantan, Tao Xu, Stanislas Polu, Alex Ray, Pranav Shyam, Aditya Ramesh, Alec Radford, Ilya Sutskever

CoRR, 2021

Zero-Shot Text-to-Image Generation.

Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Transferable Visual Models From Natural Language Supervision.

Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Clustering of Driving Encounter Scenarios Using Connected Vehicle Trajectories.

Wenshuo Wang, Aditya Ramesh, Jiacheng Zhu, Jie Li, Ding Zhao

IEEE Trans. Intell. Veh., 2020

Scaling Laws for Autoregressive Generative Modeling.

Tom Henighan, Jared Kaplan, Mor Katz, Mark Chen, Christopher Hesse, Jacob Jackson, Heewoo Jun, Tom B. Brown, Prafulla Dhariwal, Scott Gray, Chris Hallacy, Benjamin Mann, Alec Radford, Aditya Ramesh, Nick Ryder, Daniel M. Ziegler, John Schulman, Dario Amodei, Sam McCandlish

CoRR, 2020

Recurrent Neural-Linear Posterior Sampling for Non-Stationary Contextual Bandits.

Aditya Ramesh, Paulo E. Rauber, Jürgen Schmidhuber

CoRR, 2020

CompressNet: Generative Compression at Extremely Low Bitrates.

Shubham Dash, Giridharan Kumaravelu, Vijayakrishna Naganoor, Suraj Kiran Raman, Aditya Ramesh, Honglak Lee

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Language Models are Few-Shot Learners.

Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Distribution Augmentation for Generative Modeling.

Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Hotspot Mitigations for the Masses.

Fabien Hermenier, Aditya Ramesh, Abhinay Nagpal, Himanshu Shukla, Ramesh Chandra

Proceedings of the ACM Symposium on Cloud Computing, SoCC 2019, 2019

2018

A Spectral Regularizer for Unsupervised Disentanglement.

Aditya Ramesh, Youngduck Choi, Yann LeCun

CoRR, 2018

Clustering of Driving Scenarios Using Connected Vehicle Datasets.

Wenshuo Wang, Aditya Ramesh, Ding Zhao

CoRR, 2018

Backpropagation for Implicit Spectral Densities.

Aditya Ramesh, Yann LeCun

CoRR, 2018

Automatic seizure detection by modified line length and Mahalanobis distance function.

Anagh Pathak, Aditya Ramesh, Anupam Mitra, Kaushik Kumar Majumdar

Biomed. Signal Process. Control., 2018

2017

High Availability for VM Placement and a Stochastic Model for Multiple Knapsack.

Bochao Shen, Ravi Sundaram, Alexander Russell, Srinivas Aiyar, Karan Gupta, Abhinay Nagpal, Aditya Ramesh, Himanshu Shukla

Proceedings of the 26th International Conference on Computer Communication and Networks, 2017

2016

Disentangling factors of variation in deep representations using adversarial training.

Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun

CoRR, 2016

Disentangling factors of variation in deep representation using adversarial training.

Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2013

Keyword search on form results.

Aditya Ramesh, S. Sudarshan, Purva Joshi, Manisha Naik Gaonkar

VLDB J., 2013

On brewing fresh espresso: LinkedIn's distributed data serving platform.

Lin Qiao, Kapil Surlaker, Shirshanka Das, Tom Quiggle, Bob Schulman, Bhaskar Ghosh, Antony Curtis, Oliver Seeliger, Zhen Zhang, Aditya Auradkar, Chris Beaver, Gregory Brandt, Mihir Gandhi, Kishore Gopalakrishna, Wai Ip, Swaroop Jagadish, Shi Lu, Alexander Pachev, Aditya Ramesh, Abraham Sebastian, Rupa Shanbhag, Subbu Subramaniam, Yun Sun, Sajid Topiwala, Cuong Tran, Jemiah Westerman, David Zhang

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

2012

CrowdScreen: algorithms for filtering data with humans.

Aditya G. Parameswaran, Hector Garcia-Molina, Hyunjung Park, Neoklis Polyzotis, Aditya Ramesh, Jennifer Widom

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2012

2011

Keyword Search on Form Results.

Aditya Ramesh, S. Sudarshan, Purva Joshi

Proc. VLDB Endow., 2011