Search Results for author:
Found 12 papers, 4 papers with code
Single Trajectory Conformal Prediction
We study the performance of risk-controlling prediction sets (RCPS), an empirical risk minimization-based formulation of conformal prediction, with a single trajectory of temporally correlated data from an unknown stochastic dynamical system.
Early feasibility of an embedded bi-directional brain-computer interface for ambulation
Current treatments for paraplegia induced by spinal cord injury (SCI) are often limited by the severity of the injury.
Realistic Bokeh Effect Rendering on Mobile GPUs, Mobile AI & AIM 2022 challenge: Report
In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based bokeh effect rendering approach that can run on modern smartphone GPUs using TensorFlow Lite.
Bokeh-Loss GAN: Multi-Stage Adversarial Training for Realistic Edge-Aware Bokeh
We thus propose a network-based approach that is capable of rendering realistic monocular bokeh from single image inputs.
A Survey of Modern Deep Learning based Object Detection Models
Concise overview of benchmark datasets and evaluation metrics used in detection is also provided along with some of the prominent backbone architectures used in recognition tasks.
Protecting Privacy and Transforming COVID-19 Case Surveillance Datasets for Public Use
Practice Implications: Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect privacy of de-identified individuals allow for improved data use.
Cryptography and Security Computers and Society
Evaluating Attribution for Graph Neural Networks
Interpretability of machine learning models is critical to scientific understanding, AI safety, as well as debugging.
Network reinforcement driven drug repurposing for COVID-19 by exploiting disease-gene-drug associations
To reduce trial and error in finding treatments for COVID-19, we propose building a network-based drug repurposing framework to prioritize repurposable drugs.
SpikeDeep-Classifier: A deep-learning based fully automatic offline spike sorting algorithm
We proposed a novel spike sorting pipeline, based on a set of supervised and unsupervised learning algorithms.
Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces
We feed the predictions of the network back to the input to improve prediction performance and robustness.
FPGA-accelerated machine learning inference as a service for particle physics computing
New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large potential gains.
Data Analysis, Statistics and Probability High Energy Physics - Experiment Computational Physics Instrumentation and Detectors
Situational Awareness based Risk-Adapatable Access Control in Enterprise Networks
As the computing landscape evolves towards distributed architectures such as Internet of Things (IoT), enterprises are moving away from traditional perimeter based security models toward so called zero trust networking (ZTN) models that treat both the intranet and Internet as equally untrustworthy.
Cryptography and Security
