Science on HAL

Publications

Journals

1. Graber, Colin, and Alexander Schwing. "Graph Structured Prediction Energy Networks." Advances in Neural Information Processing Systems. 2019.
2. Burke, Colin J., et al. "Deblending and classifying astronomical sources with Mask R-CNN deep learning." Monthly Notices of the Royal Astronomical Society 490.3 (2019): 3952-3965.
3. Fang, Tiantian, and Alexander Schwing. "Co-Generation with GANs using AIS based HMC." Advances in Neural Information Processing Systems. 2019.
4. Wei, Wei, and E. A. Huerta. "Gravitational wave denoising of binary black hole mergers with deep learning." Physics Letters B 800 (2020): 135081.
5. Lin, Jingxiang, Unnat Jain, and Alexander Schwing. "TAB-VCR: Tags and Attributes based VCR Baselines." Advances in Neural Information Processing Systems. 2019.
6. Teixeira, Thiago SFX, William Gropp, and David Padua. "Managing code transformations for better performance portability." The International Journal of High Performance Computing Applications 33.6 (2019): 1290-1306.
7. Wei, Wei, et al. "Deep transfer learning for star cluster classification: I. application to the PHANGS–HST survey." Monthly Notices of the Royal Astronomical Society 493.3 (2020): 3178-3193.

Proceedings

1. Hashemi, Sayed Hadi, et al. "tensorflow-tracing: A Performance Tuning Framework for Production." 2019 {USENIX} Conference on Operational Machine Learning (OpML 19). 2019.
2. Pearson, Carl, et al. "Update on Triangle Counting on GPU." 2019 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2019.
3. Mailthody, Vikram S., et al. "Collaborative (cpu+ gpu) algorithms for triangle counting and truss decomposition." 2018 IEEE High Performance extreme Computing Conference (HPEC). IEEE, 2018.
4. Almasri, Mohammad, et al. "Update on k-truss Decomposition on GPU." 2019 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2019.
5. Misra, Ashish, and Volodymyr Kindratenko. "HLS-Based Acceleration Framework for Deep Convolutional Neural Networks." International Symposium on Applied Reconfigurable Computing. Springer, Cham, 2020.
6. Yeh, Raymond A., Yuan-Ting Hu, and Alexander G. Schwing. "Chirality Nets: Exploiting Structure in Human Pose Regression." Conference on Advances in Neural Information Processing Systems Workshop (NeurIPSW). 2019.

Archives

1. Gupta, Arjun, et al. "Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms." arXiv preprint arXiv:1912.07618 (2019).
2. Wei, Wei, et al. "Deep Transfer Learning for Star Cluster Classification: I. Application to the PHANGS-HST Survey." arXiv preprint arXiv:1909.02024 (2019).
3. Kothari, Konik, et al. "Random mesh projectors for inverse problems." (2018).
4. Luo, Shirui, et al. "Review and Examination of Input Feature Preparation Methods and Machine Learning Models for Turbulence Modeling." arXiv preprint arXiv:2001.05485 (2020).
5. Graber, Colin, et al. "Unsupervised Discovery of Dynamic Neural Circuits." (2019).
6. Yeh, Raymond A., Yuan-Ting Hu, and Alexander G. Schwing. "Chirality Nets: Exploiting Structure in Human Pose Regression."
7. Liu, Iou-Jen, Raymond A. Yeh, and Alexander G. Schwing. "PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning." arXiv preprint arXiv:1911.00025 (2019).
8. Lin, Jingxiang, Unnat Jain, and Alexander G. Schwing. "A Simple Baseline for Visual Commonsense Reasoning."
9. Lin, Jingxiang, Unnat Jain, and Alexander Schwing. "TAB-VCR: Tags and Attributes for Visual Commonsense Reasoning." (2019).
10. Carrasquilla, Juan, et al. "Probabilistic Simulation of Quantum Circuits with the Transformer." arXiv preprint arXiv:1912.11052 (2019).
11. Shen, Hongyu, et al. "Deterministic and Bayesian Neural Networks for Low-latency Gravitational Wave Parameter Estimation of Binary Black Hole Mergers." arXiv preprint arXiv:1903.01998 (2019).

Presentations

Posters

1. Graber, Colin, et al. "Unsupervised Discovery of Dynamic Neural Circuits." NeurIPS 2019 Workshop Neuro AI Paper28, (2019).