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Aditya Ramesh
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2020 – today
- 2023
- [j7]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): 1-17 (2023) - [c14]Francesco Faccio, Vincent Herrmann, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber:
Goal-Conditioned Generators of Deep Policies. AAAI 2023: 7503-7511 - [c13]Kenny John Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber:
The Benefits of Model-Based Generalization in Reinforcement Learning. ICML 2023: 40254-40276 - [i18]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 abs/2305.17066 (2023) - 2022
- [j6]Aditya Ramesh, Paulo E. Rauber, Michelangelo Conserva, Jürgen Schmidhuber:
Recurrent Neural-Linear Posterior Sampling for Nonstationary Contextual Bandits. Neural Comput. 34(11): 2232-2272 (2022) - [j5]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): 4957 (2022) - [c12]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: 16784-16804 - [c11]Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber:
Exploring through Random Curiosity with General Value Functions. NeurIPS 2022 - [i17]Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen:
Hierarchical Text-Conditional Image Generation with CLIP Latents. CoRR abs/2204.06125 (2022) - [i16]Francesco Faccio, Aditya Ramesh, Vincent Herrmann, Jean Harb, Jürgen Schmidhuber:
General Policy Evaluation and Improvement by Learning to Identify Few But Crucial States. CoRR abs/2207.01566 (2022) - [i15]Francesco Faccio, Vincent Herrmann, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber:
Goal-Conditioned Generators of Deep Policies. CoRR abs/2207.01570 (2022) - [i14]Kenny Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber:
The Benefits of Model-Based Generalization in Reinforcement Learning. CoRR abs/2211.02222 (2022) - [i13]Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber:
Exploring through Random Curiosity with General Value Functions. CoRR abs/2211.10282 (2022) - 2021
- [c10]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: 8748-8763 - [c9]Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever:
Zero-Shot Text-to-Image Generation. ICML 2021: 8821-8831 - [i12]Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever:
Zero-Shot Text-to-Image Generation. CoRR abs/2102.12092 (2021) - [i11]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 abs/2103.00020 (2021) - [i10]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 abs/2110.05448 (2021) - [i9]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 abs/2112.10741 (2021) - 2020
- [j4]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): 485-496 (2020) - [c8]Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever:
Distribution Augmentation for Generative Modeling. ICML 2020: 5006-5019 - [c7]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 - [c6]Shubham Dash, Giridharan Kumaravelu, Vijayakrishna Naganoor, Suraj Kiran Raman, Aditya Ramesh
, Honglak Lee:
CompressNet: Generative Compression at Extremely Low Bitrates. WACV 2020: 2314-2322 - [i8]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 abs/2005.14165 (2020) - [i7]Suraj Kiran Raman, Aditya Ramesh, Vijayakrishna Naganoor, Shubham Dash, Giridharan Kumaravelu, Honglak Lee:
CompressNet: Generative Compression at Extremely Low Bitrates. CoRR abs/2006.08003 (2020) - [i6]Aditya Ramesh, Paulo E. Rauber, Jürgen Schmidhuber:
Recurrent Neural-Linear Posterior Sampling for Non-Stationary Contextual Bandits. CoRR abs/2007.04750 (2020) - [i5]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 abs/2010.14701 (2020)
2010 – 2019
- 2019
- [c5]Fabien Hermenier, Aditya Ramesh, Abhinay Nagpal, Himanshu Shukla, Ramesh Chandra:
Hotspot Mitigations for the Masses. SoCC 2019: 102-113 - 2018
- [j3]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: 279-287 (2018) - [i4]Aditya Ramesh, Yann LeCun:
Backpropagation for Implicit Spectral Densities. CoRR abs/1806.00499 (2018) - [i3]Wenshuo Wang, Aditya Ramesh, Ding Zhao:
Clustering of Driving Scenarios Using Connected Vehicle Datasets. CoRR abs/1807.08415 (2018) - [i2]Aditya Ramesh, Youngduck Choi, Yann LeCun:
A Spectral Regularizer for Unsupervised Disentanglement. CoRR abs/1812.01161 (2018) - 2017
- [c4]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: 1-9 - 2016
- [c3]Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun:
Disentangling factors of variation in deep representation using adversarial training. NIPS 2016: 5041-5049 - [i1]Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun:
Disentangling factors of variation in deep representations using adversarial training. CoRR abs/1611.03383 (2016) - 2013
- [j2]Aditya Ramesh, S. Sudarshan, Purva Joshi, Manisha Naik Gaonkar:
Keyword search on form results. VLDB J. 22(1): 99-123 (2013) - [c2]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: 1135-1146 - 2012
- [c1]Aditya G. Parameswaran
, Hector Garcia-Molina, Hyunjung Park, Neoklis Polyzotis, Aditya Ramesh, Jennifer Widom:
CrowdScreen: algorithms for filtering data with humans. SIGMOD Conference 2012: 361-372 - 2011
- [j1]Aditya Ramesh, S. Sudarshan, Purva Joshi:
Keyword Search on Form Results. Proc. VLDB Endow. 4(11): 1189-1200 (2011)
Coauthor Index
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