Peter Chin

发表

Neural Network Optimization with Biologically Inspired Low-Dimensional Manifold Learning

Sylee Dandekar, Hieu Le, Andrew Wood, 2021, 2021 International Conference on Computational Science and Computational Intelligence (CSCI).

Dreaming with ARC

T. Poggio, Andrzej Banburski, Simon Alford, 2020 .

A Study on Self-Supervised Object Detection Pretraining

M. Khademi, Peter Chin, Simon Kornblith, 2022, 2207.04186.

Neural Network Optimization with Biologically Inspired Low-Dimensional Manifold Learning

Sylee Dandekar, Hieu Le, Andrew Wood, 2021, 2021 International Conference on Computational Science and Computational Intelligence (CSCI).

Cs-net: Structural Approach to Time-series Forecasting for High-dimensional Feature Space Data with Limited Observations

Peter Chin, Weiyu Zong, Mingqian Feng, 2022, ArXiv.

A Study on Self-Supervised Object Detection Pretraining

Simon Kornblith, M. Khademi, Peter Chin, 2022, ECCV Workshops.

Revealing and Protecting Labels in Distributed Training pdf

Swaroop Ramaswamy, Rajiv Mathews, Om Thakkar, 2021, NeurIPS.

A Multi-scale Graph Signature for Persistence Diagrams based on Return Probabilities of Random Walks

Trung D. Q. Dang, Peter Chin, Chau Pham, 2022, ArXiv.

Substitutional Neural Image Compression pdf

Brian Kulis, Wei Wang, Wei Jiang, 2021, 2022 Picture Coding Symposium (PCS).

Learning to Repair Software Vulnerabilities with Generative Adversarial Networks

Sang Peter Chin, Onur Ozdemir, Jacob Harer, 2018, NeurIPS.

GymFG: A Framework with a Gym Interface for FlightGear pdf

Ali Sydney, Bishal Thapa, Peter Chin, 2020, ArXiv.

Stochastic Block Model and Community Detection in Sparse Graphs: A spectral algorithm with optimal rate of recovery

Anup Rao, Van H. Vu, Peter Chin, 2015, COLT.

Tree-Transformer: A Transformer-Based Method for Correction of Tree-Structured Data pdf

Peter Chin, Jacob Harer, Chris Reale, 2019, ArXiv.

Mixed Spatio-Temporal Neural Networks on Real-time Prediction of Crimes

Peter Chin, Xiao Zhou, Chengche Wang, 2021, International Conference on Machine Learning and Applications.

On the Transition from Neural Representation to Symbolic Knowledge

Peter Chin, Junyan Cheng, Peter Chin, 2023, ArXiv.

Deep learning-based classification and anomaly detection of side-channel signals

Gavin Brown, Quan Zhou, John Wang, 2018, Defense + Security.

RECONSTRUCTION-FREE DEEP CONVOLUTIONAL NEURAL NETWORKS FOR PARTIALLY OBSERVED IMAGES

Trac D. Tran, Sang Peter Chin, Muyinatu A. Lediju Bell, 2018, 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Automated software vulnerability detection with machine learning pdf

Sang Peter Chin, Akshay Rangamani, Onur Ozdemir, 2018, ArXiv.

Generalizing Topological Graph Neural Networks with Paths

Peter Chin, Quang Truong, Peter Chin, 2023, ArXiv.

Adversarial Transformer Language Models for Contextual Commonsense Inference

H. Lieberman, C. Breazeal, Pedro Colon-Hernandez, 2023, ArXiv.

RetroGAN: A Cyclic Post-Specialization System for Improving Out-of-Knowledge and Rare Word Representations pdf

Henry Lieberman, Catherine Havasi, Pedro Colon-Hernandez, 2021, FINDINGS.

What is Learned in Knowledge Graph Embeddings? pdf

Michael Simkin, Omri Ben-Eliezer, Tianqi Wu, 2021, COMPLEX NETWORKS.

Reinforcement Learning in FlipIt pdf

Peter Chin, Laura Greige, Peter Chin, 2020, ArXiv.

Computing Diffusion State Distance Using Green's Function and Heat Kernel on Graphs

Linyuan Lu, Amit Sinha, Peter Chin, 2014, WAW.

Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes

Peter Chin, Quang Truong, 2023, 2308.06838.

Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis

Sarel Cohen, Daniel Waddington, Moshik Hershcovitch, 2021, 2021 IEEE High Performance Extreme Computing Conference (HPEC).