Aditya Ramesh

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 36

Top Topics

Metropolis Hastings

Image Generation

Diffusion Models

Top Venues

Publications

Francesco Faccio, Vincent Herrmann, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber
Goal-Conditioned Generators of Deep Policies. AAAI (2023)
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
Mindstorms in Natural Language-Based Societies of Mind. CoRR (2023)
Nikola Banovic, Zhuoran Yang, Aditya Ramesh, Alice Liu
Being Trustworthy is Not Enough: How Untrustworthy Artificial Intelligence (AI) Can Deceive the End-Users and Gain Their Trust. Proc. ACM Hum. Comput. Interact. 7 (CSCW1) (2023)
Kenny John Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber
The Benefits of Model-Based Generalization in Reinforcement Learning. ICML (2023)
Francesco Faccio, Vincent Herrmann, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber
Goal-Conditioned Generators of Deep Policies. CoRR (2022)
Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. ICML (2022)
Kenny Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber
The Benefits of Model-Based Generalization in Reinforcement Learning. CoRR (2022)
Aditya Ramesh, Paulo E. Rauber, Michelangelo Conserva, Jürgen Schmidhuber
Recurrent Neural-Linear Posterior Sampling for Nonstationary Contextual Bandits. Neural Comput. 34 (11) (2022)
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen
Hierarchical Text-Conditional Image Generation with CLIP Latents. CoRR (2022)
Francesco Faccio, Aditya Ramesh, Vincent Herrmann, Jean Harb, Jürgen Schmidhuber
General Policy Evaluation and Improvement by Learning to Identify Few But Crucial States. CoRR (2022)
Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber
Exploring through Random Curiosity with General Value Functions. NeurIPS (2022)
Christian Greve, Hobey Tam, Manfred G. Grabherr, Aditya Ramesh, Bart Scheerder, Juha M. Hijmans
Flexible Machine Learning Algorithms for Clinical Gait Assessment Tools. Sensors 22 (13) (2022)
Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber
Exploring through Random Curiosity with General Value Functions. CoRR (2022)
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
Learning Transferable Visual Models From Natural Language Supervision. CoRR (2021)
Jesse Michael Han, Igor Babuschkin, Harrison Edwards, Arvind Neelakantan, Tao Xu, Stanislas Polu, Alex Ray, Pranav Shyam, Aditya Ramesh, Alec Radford, Ilya Sutskever
Unsupervised Neural Machine Translation with Generative Language Models Only. CoRR (2021)
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever
Zero-Shot Text-to-Image Generation. ICML (2021)
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
Learning Transferable Visual Models From Natural Language Supervision. ICML (2021)
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. CoRR (2021)
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever
Zero-Shot Text-to-Image Generation. CoRR (2021)
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
Language Models are Few-Shot Learners. NeurIPS (2020)
Suraj Kiran Raman, Aditya Ramesh, Vijayakrishna Naganoor, Shubham Dash, Giridharan Kumaravelu, Honglak Lee
CompressNet: Generative Compression at Extremely Low Bitrates. CoRR (2020)
Wenshuo Wang, Aditya Ramesh, Jiacheng Zhu, Jie Li, Ding Zhao
Clustering of Driving Encounter Scenarios Using Connected Vehicle Trajectories. IEEE Trans. Intell. Veh. 5 (3) (2020)
Aditya Ramesh, Paulo E. Rauber, Jürgen Schmidhuber
Recurrent Neural-Linear Posterior Sampling for Non-Stationary Contextual Bandits. CoRR (2020)
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
Language Models are Few-Shot Learners. CoRR (2020)
Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever
Distribution Augmentation for Generative Modeling. ICML (2020)
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
Scaling Laws for Autoregressive Generative Modeling. CoRR (2020)
Shubham Dash, Giridharan Kumaravelu, Vijayakrishna Naganoor, Suraj Kiran Raman, Aditya Ramesh, Honglak Lee
CompressNet: Generative Compression at Extremely Low Bitrates. WACV (2020)
Fabien Hermenier, Aditya Ramesh, Abhinay Nagpal, Himanshu Shukla, Ramesh Chandra
Hotspot Mitigations for the Masses. SoCC (2019)
Himanshu Shukla, Abhinay Nagpal, Ramesh Chandra, Aditya Ramesh, Fabien Hermenier
Hotspot Mitigations for the Masses. SoCC (2019)
Aditya Ramesh, Youngduck Choi, Yann LeCun
A Spectral Regularizer for Unsupervised Disentanglement. CoRR (2018)
Aditya Ramesh, Yann LeCun
Backpropagation for Implicit Spectral Densities. CoRR (2018)
Wenshuo Wang, Aditya Ramesh, Ding Zhao
Clustering of Driving Scenarios Using Connected Vehicle Datasets. CoRR (2018)
Anagh Pathak, Aditya Ramesh, Anupam Mitra, Kaushik Kumar Majumdar
Automatic seizure detection by modified line length and Mahalanobis distance function. Biomed. Signal Process. Control. 44 (2018)
Bochao Shen, Ravi Sundaram, Alexander Russell, Srinivas Aiyar, Karan Gupta, Abhinay Nagpal, Aditya Ramesh, Himanshu Shukla
High Availability for VM Placement and a Stochastic Model for Multiple Knapsack. ICCCN (2017)
Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun
Disentangling factors of variation in deep representations using adversarial training. CoRR (2016)
Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun
Disentangling factors of variation in deep representation using adversarial training. NIPS (2016)
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
On brewing fresh espresso: LinkedIn's distributed data serving platform. SIGMOD Conference (2013)
Aditya Ramesh, S. Sudarshan, Purva Joshi, Manisha Naik Gaonkar
Keyword search on form results. VLDB J. 22 (1) (2013)
Aditya G. Parameswaran, Hector Garcia-Molina, Hyunjung Park, Neoklis Polyzotis, Aditya Ramesh, Jennifer Widom
CrowdScreen: algorithms for filtering data with humans. SIGMOD Conference (2012)
Aditya Ramesh, S. Sudarshan, Purva Joshi
Keyword Search on Form Results. Proc. VLDB Endow. 4 (11) (2011)