Gpt-4 technical report J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ... arXiv preprint arXiv:2303.08774, 2023 | 6199 | 2023 |
Evaluating large language models trained on code M Chen, J Tworek, H Jun, Q Yuan, HPDO Pinto, J Kaplan, H Edwards, ... arXiv preprint arXiv:2107.03374, 2021 | 3406 | 2021 |
An intriguing failing of convolutional neural networks and the coordconv solution R Liu, J Lehman, P Molino, F Petroski Such, E Frank, A Sergeev, ... Advances in neural information processing systems 31, 2018 | 1028 | 2018 |
Deep neuroevolution: Genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning FP Such, V Madhavan, E Conti, J Lehman, KO Stanley, J Clune arXiv preprint arXiv:1712.06567, 2017 | 944 | 2017 |
Improving exploration in evolution strategies for deep reinforcement learning via a population of novelty-seeking agents E Conti, V Madhavan, F Petroski Such, J Lehman, K Stanley, J Clune Advances in neural information processing systems 31, 2018 | 428 | 2018 |
Text and code embeddings by contrastive pre-training A Neelakantan, T Xu, R Puri, A Radford, JM Han, J Tworek, Q Yuan, ... arXiv preprint arXiv:2201.10005, 2022 | 405 | 2022 |
Intelligent character recognition using fully convolutional neural networks R Ptucha, FP Such, S Pillai, F Brockler, V Singh, P Hutkowski Pattern recognition 88, 604-613, 2019 | 189 | 2019 |
Generative teaching networks: Accelerating neural architecture search by learning to generate synthetic training data FP Such, A Rawal, J Lehman, K Stanley, J Clune International Conference on Machine Learning, 9206-9216, 2020 | 186 | 2020 |
Robust spatial filtering with graph convolutional neural networks FP Such, S Sah, MA Dominguez, S Pillai, C Zhang, A Michael, ND Cahill, ... IEEE Journal of Selected Topics in Signal Processing 11 (6), 884-896, 2017 | 184 | 2017 |
An atari model zoo for analyzing, visualizing, and comparing deep reinforcement learning agents FP Such, V Madhavan, R Liu, R Wang, PS Castro, Y Li, J Zhi, L Schubert, ... arXiv preprint arXiv:1812.07069, 2018 | 65 | 2018 |
Evaluating large language models trained on code. arXiv 2021 M Chen, J Tworek, H Jun, Q Yuan, HPO Pinto, J Kaplan, H Edwards, ... arXiv preprint arXiv:2107.03374 10, 2021 | 56 | 2021 |
Generalized hidden parameter mdps: Transferable model-based rl in a handful of trials C Perez, FP Such, T Karaletsos Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5403-5411, 2020 | 45 | 2020 |
System and method of character recognition using fully convolutional neural networks FP Such, R Ptucha, F Brockler, P Hutkowski, V Singh US Patent 10,936,862, 2021 | 32 | 2021 |
Fully convolutional networks for handwriting recognition FP Such, D Peri, F Brockler, H Paul, R Ptucha 2018 16th International Conference on Frontiers in Handwriting Recognition …, 2018 | 31 | 2018 |
Gpt-4o system card A Hurst, A Lerer, AP Goucher, A Perelman, A Ramesh, A Clark, AJ Ostrow, ... arXiv preprint arXiv:2410.21276, 2024 | 27 | 2024 |
System and method of character recognition using fully convolutional neural networks with attention FP Such, R Ptucha, F Brockler, P Hutkowski US Patent 10,846,523, 2020 | 26 | 2020 |
Efficient transfer learning and online adaptation with latent variable models for continuous control CF Perez, FP Such, T Karaletsos arXiv preprint arXiv:1812.03399, 2018 | 20 | 2018 |
Towards 3d convolutional neural networks with meshes M Dominguez, FP Such, S Sah, R Ptucha 2017 IEEE international conference on image processing (ICIP), 3929-3933, 2017 | 17 | 2017 |
Synthetic petri dish: a novel surrogate model for rapid architecture search A Rawal, J Lehman, FP Such, J Clune, KO Stanley arXiv preprint arXiv:2005.13092, 2020 | 5 | 2020 |
Temporally steered gaussian attention for video understanding S Sah, T Nguyen, M Dominguez, F Petroski Such, R Ptucha Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 4 | 2017 |