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ORCIDEdward Kim 0006
Person information
- affiliation: Drexel University, Department of Computer Science, Philadelphia, PA, USA
- affiliation: Villanova University, Department of Computing Sciences, PA, USA
Other persons with the same name
- Edward Kim — disambiguation page
- Edward J. Kim 0001
![[0000-0002-9828-4624]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-9828-4624")
(aka: Edward Kim 0001) — NASA Goddard Space Flight Center, GSFC, Hydrological Sciences Laboratory, Greenbelt, MD, USA (and 1 more) - Edward Kim 0004 — Massachusetts Institute of Technology, Department of Materials Science and Engineering, Cambridge, MA, USA
- Edward Kim 0005 — University of California, Berkeley, CA, USA
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Journal Articles
- 2024
[j3]Eric Plitman, Edward Kim, Rajesh Patel, Seema Kohout, Rongyu Jin, Vincent Chan, Michael Dinsmore:
Development of an Automated and Scalable Virtual Assistant to Aid in PPE Adherence: A Study with Implications for Applications within Anesthesiology. J. Medical Syst. 48(1): 7 (2024)- 2023
- [j2]Satvik Tripathi, Alisha Isabelle Augustin, Farouk Dako, Edward Kim:
Turing test-inspired method for analysis of biases prevalent in artificial intelligence-based medical imaging. AI Ethics 3(4): 1193-1201 (2023) - [j1]Maryam Daniali, Peter D. Galer, David Lewis-Smith, Shridhar Parthasarathy, Edward Kim, Dario D. Salvucci, Jeffrey M. Miller, Scott Haag, Ingo Helbig:
Enriching representation learning using 53 million patient notes through human phenotype ontology embedding. Artif. Intell. Medicine 139: 102523 (2023)
Conference and Workshop Papers
- 2024
- [c23]Darryl Hannan, Ragib Arnab, Gavin Parpart, Garrett T. Kenyon, Edward Kim, Yijing Watkins:
Event-To-Video Conversion for Overhead Object Detection. SSIAI 2024: 89-92 - 2023
- [c22]Darryl Hannan, Steven C. Nesbit, Ximing Wen, Glen Smith, Qiao Zhang, Alberto Goffi, Vincent Chan, Michael J. Morris, John C. Hunninghake, Nicholas E. Villalobos, Edward Kim, Rosina O. Weber, Christopher J. MacLellan:
MobilePTX: Sparse Coding for Pneumothorax Detection Given Limited Training Examples. AAAI 2023: 15675-15681 - [c21]Andrew O'Brien, Edward Kim, Rosina Weber:
Basis Learning for Dynamical Systems in the Presence of Incomplete Scientific Knowledge. AIKE 2023: 28-32 - [c20]Andrew O'Brien, Edward Kim, Rosina Weber:
Investigating Causally Augmented Sparse Learning as a Tool for Meaningful Classification. AIKE 2023: 33-37 - [c19]Edward Kim, Lucy Robinson, Isamu Isozaki, Noreen Robertson, Charles B. Cairns, Satvik Tripathi, Vicki Seyfert-Margolis:
A Coronavirus Cohort Case Study - Dataset Trends using Machine Learning Methods. BIBM 2023: 4213-4219 - [c18]Maryam Daniali, Edward Kim:
Perception Over Time: Temporal Dynamics for Robust Image Understanding. CVPR Workshops 2023: 5656-5665 - [c17]Andrew O'Brien, Rosina Weber, Edward Kim:
Investigating SINDy as a Tool for Causal Discovery in Time Series Signals. ICASSP 2023: 1-5 - 2022
- [c16]Andrew O'Brien, Edward Kim:
Toward Multi-Agent Algorithmic Recourse Challenges From a Game-Theoretic Perspective. FLAIRS 2022 - [c15]Gavin Parpart, Carlos González Rivera, Terrence C. Stewart, Edward Kim, Jocelyn Rego, Andrew O'Brien, Steven C. Nesbit, Garrett T. Kenyon, Yijing Watkins:
Dictionary Learning with Accumulator Neurons. ICONS 2022: 11:1-11:9 - [c14]Steven C. Nesbit, Andrew O'Brien, Jocelyn Rego, Gavin Parpart, Carlos González Rivera, Garrett T. Kenyon, Edward Kim, Terrence C. Stewart, Yijing Watkins:
Think Fast: Time Control in Varying Paradigms of Spiking Neural Networks. ICONS 2022: 21:1-21:8 - [c13]Edward Kim, Trang Ha, Garrett T. Kenyon:
Sparse Kernel Transfer Learning. ISVC (2) 2022: 39-52 - [c12]Connor Onweller, Andrew O'Brien, Edward Kim, Kathleen F. McCoy:
Distributional Semantics of Line Charts for Trend Classification. ISVC (2) 2022: 259-269 - 2021
- [c11]T. Haj Mohamad, Amirhassan Abbasi, Edward Kim, Chandrasekhar Nataraj:
Application of Deep CNN-LSTM Network to Gear Fault Diagnostics. ICPHM 2021: 1-6 - [c10]Nicki Barari, Edward Kim:
Linking Sparse Coding Dictionaries for Representation Learning. ICRC 2021: 84-87 - [c9]Yigit Alparslan, Ethan Jacob Moyer, Isamu Mclean Isozaki, Daniel Schwartz, Adam Dunlop, Shesh Dave, Edward Kim:
Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems. IJCNN 2021: 1-8 - 2020
- [c8]Yijing Watkins, Edward Kim, Andrew Sornborger, Garrett T. Kenyon:
Using Sinusoidally-Modulated Noise as a Surrogate for Slow-Wave Sleep to Accomplish Stable Unsupervised Dictionary Learning in a Spike-Based Sparse Coding Model. CVPR Workshops 2020: 1482-1487 - [c7]Edward Kim, Jocelyn Rego, Yijing Watkins, Garrett T. Kenyon:
Modeling Biological Immunity to Adversarial Examples. CVPR 2020: 4665-4674 - [c6]John Carter, Jocelyn Rego, Daniel Schwartz, Vikas Bhandawat, Edward Kim:
Learning Spiking Neural Network Models of Drosophila Olfaction. ICONS 2020: 20:1-20:5 - [c5]Edward Kim, Connor Onweller, Kathleen F. McCoy:
Information Graphic Summarization using a Collection of Multimodal Deep Neural Networks. ICPR 2020: 10188-10195 - [c4]Daniel Schwartz, Yigit Alparslan, Edward Kim:
Regularization and Sparsity for Adversarial Robustness and Stable Attribution. ISVC (1) 2020: 3-14 - 2019
- [c3]Edward Kim, Jessica Yarnall, Priya Shah, Garrett T. Kenyon:
A Neuromorphic Sparse Coding Defense to Adversarial Images. ICONS 2019: 12:1-12:8 - 2018
- [c2]Edward Kim, Kathleen F. McCoy:
Multimodal Deep Learning using Images and Text for Information Graphic Classification. ASSETS 2018: 143-148 - [c1]Edward Kim, Darryl Hannan, Garrett T. Kenyon:
Deep Sparse Coding for Invariant Multimodal Halle Berry Neurons. CVPR 2018: 1111-1120
Informal and Other Publications
- 2024
- [i18]Darryl Hannan, Ragib Arnab, Gavin Parpart, Garrett T. Kenyon, Edward Kim, Yijing Watkins:
Event-to-Video Conversion for Overhead Object Detection. CoRR abs/2402.06805 (2024) - [i17]Darryl Hannan, Steven C. Nesbit, Ximing Wen, Glen Smith, Qiao Zhang, Alberto Goffi, Vincent Chan, Michael J. Morris, John C. Hunninghake, Nicholas E. Villalobos, Edward Kim, Rosina O. Weber, Christopher J. MacLellan:
Interpretable Models for Detecting and Monitoring Elevated Intracranial Pressure. CoRR abs/2403.02236 (2024) - 2023
- [i16]Edward Kim, Isamu Isozaki, Naomi Sirkin, Michael P. Robson:
Generative Artificial Intelligence Consensus in a Trustless Network. CoRR abs/2307.01898 (2023) - 2022
- [i15]Maryam Daniali, Edward Kim:
Perception Over Time: Temporal Dynamics for Robust Image Understanding. CoRR abs/2203.06254 (2022) - [i14]Ethan Jacob Moyer, Alisha Isabelle Augustin, Satvik Tripathi, Ansh Aashish Dholakia, Andy Nguyen, Isamu Mclean Isozaki, Daniel Schwartz, Edward Kim:
EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting. CoRR abs/2204.07066 (2022) - [i13]Gavin Parpart, Carlos González Rivera, Terrence C. Stewart, Edward Kim, Jocelyn Rego, Andrew O'Brien, Steven C. Nesbit, Garrett T. Kenyon, Yijing Watkins:
Dictionary Learning with Accumulator Neurons. CoRR abs/2205.15386 (2022) - [i12]Darryl Hannan, Steven C. Nesbit, Ximing Wen, Glen Smith, Qiao Zhang, Alberto Goffi, Vincent Chan, Michael J. Morris, John C. Hunninghake, Nicholas E. Villalobos, Edward Kim, Rosina O. Weber, Christopher J. MacLellan:
MobilePTX: Sparse Coding for Pneumothorax Detection Given Limited Training Examples. CoRR abs/2212.03282 (2022) - [i11]Andrew O'Brien, Rosina Weber, Edward Kim:
Investigating Sindy As a Tool For Causal Discovery In Time Series Signals. CoRR abs/2212.14133 (2022) - 2021
- [i10]Yigit Alparslan, Ethan Jacob Moyer, Isamu Mclean Isozaki, Daniel Schwartz, Adam Dunlop, Shesh Dave, Edward Kim:
Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems. CoRR abs/2101.06511 (2021) - [i9]Yigit Alparslan, Ethan Jacob Moyer, Edward Kim:
Evaluating Online and Offline Accuracy Traversal Algorithms for k-Complete Neural Network Architectures. CoRR abs/2101.06518 (2021) - [i8]Yigit Alparslan, Edward Kim:
Robust SleepNets. CoRR abs/2102.12555 (2021) - [i7]Yigit Alparslan, Edward Kim:
Extreme Volatility Prediction in Stock Market: When GameStop meets Long Short-Term Memory Networks. CoRR abs/2103.01121 (2021) - [i6]Ethan Jacob Moyer, Jeff Winchell, Isamu Isozaki, Yigit Alparslan, Mali Halac, Edward Kim:
Functional Protein Structure Annotation Using a Deep Convolutional Generative Adversarial Network. CoRR abs/2104.08969 (2021) - [i5]Yigit Alparslan, Edward Kim:
ATRAS: Adversarially Trained Robust Architecture Search. CoRR abs/2106.06917 (2021) - 2020
- [i4]Edward Kim, Maryam Daniali, Jocelyn Rego, Garrett T. Kenyon:
The Selectivity and Competition of the Mind's Eye in Visual Perception. CoRR abs/2011.11167 (2020) - [i3]Edward Kim, Connor Onweller, Andrew O'Brien, Kathleen F. McCoy:
The Interpretable Dictionary in Sparse Coding. CoRR abs/2011.11805 (2020) - 2018
- [i2]Jacob M. Springer, Charles M. S. Strauss, Austin M. Thresher, Edward Kim, Garrett T. Kenyon:
Classifiers Based on Deep Sparse Coding Architectures are Robust to Deep Learning Transferable Examples. CoRR abs/1811.07211 (2018) - 2017
- [i1]Edward Kim, Darryl Hannan, Garrett T. Kenyon:
Deep Sparse Coding for Invariant Multimodal Halle Berry Neurons. CoRR abs/1711.07998 (2017)
Coauthor Index
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