Understanding Gaussian noise injections in neural networks

Understanding Gaussian noise injections in neural networks

<p>Deep Learning (read neural networks) has emerged as one of the most exciting and powerful tools in the statistical machine learning toolbox. Neural networks over the past decade have defeated incumbent state of the art models in computer vision, natural language processing, and reinforcemen...

Bibliografski detalji
Glavni autor:	Camuto, A
Daljnji autori:	Holmes, C
Format:	Disertacija
Jezik:	English
Izdano:	2021
Teme:	Deep learning (Machine learning)

Slični predmeti

Resilience of Machine Learning Models in Anxiety Detection: Assessing the Impact of Gaussian Noise on Wearable Sensors
od: Abdulrahman Alkurdi, i dr.
Izdano: (2024-12-01)

Neural networks as data
od: Dupont, E
Izdano: (2022)

Efficient neural network verification and training
od: De Palma, A
Izdano: (2023)

On kernel and feature learning in neural networks
od: He, B
Izdano: (2022)

Neural networks for inference, inference for neural networks
od: Webb, S
Izdano: (2018)

Towards robust neural networks: evaluation and construction
od: Lu, J
Izdano: (2021)

Measuring Laser Beams with a Neural Network (Data)
od: Hofer, L, i dr.
Izdano: (2022)

Towards robust machine learning with graph neural networks
od: Jaeckle, F
Izdano: (2022)

Towards efficient and reliable neural networks
od: de Jorge Aranda, P
Izdano: (2024)

When the state of the art is ahead of the state of understanding: Unintuitive properties of deep neural networks
od: Joan Serrà
Izdano: (2019-03-01)

Understanding approximation for Bayesian inference in neural networks
od: Farquhar, S
Izdano: (2022)

Additive Ensemble Neural Networks
od: Minyoung Park, i dr.
Izdano: (2020-01-01)

Employee Attrition Prediction Using Deep Neural Networks
od: Salah Al-Darraji, i dr.
Izdano: (2021-11-01)

AI-driven convolutional neural networks for accurate identification of yellow fever vectors
od: Taís Oliveira de Araújo, i dr.
Izdano: (2024-08-01)

An Efficient Optimization Technique for Training Deep Neural Networks
od: Faisal Mehmood, i dr.
Izdano: (2023-03-01)

Towards diverse generation and reliable classification using neural networks
od: Kulharia, V
Izdano: (2022)

Explainable Convolutional Neural Networks for Brain Cancer Detection and Localisation
od: Francesco Mercaldo, i dr.
Izdano: (2023-09-01)

Deep vision for indoor understanding and localisation
od: Howard-Jenkins, H
Izdano: (2022)

Theoretical Understanding of Convolutional Neural Network: Concepts, Architectures, Applications, Future Directions
od: Mohammad Mustafa Taye
Izdano: (2023-03-01)

Sign language understanding using multimodal learning
od: Momeni, L
Izdano: (2024)

End-to-end learning, and audio-visual human-centric video understanding
od: Brown, A
Izdano: (2022)

Communicating Neural Network architectures for resource constrained systems
od: Abudu, P
Izdano: (2022)

Trinity: Neural Network Adaptive Distributed Parallel Training Method Based on Reinforcement Learning
od: Yan Zeng, i dr.
Izdano: (2022-03-01)

Does the FARNet neural network algorithm accurately identify Posteroanterior cephalometric landmarks?
od: Merve Gonca, i dr.
Izdano: (2024-10-01)

Extraction of Features for Time Series Classification Using Noise Injection
od: Gyu Il Kim, i dr.
Izdano: (2024-10-01)

Optimising convolutional neural networks for large-scale neuroimaging studies
od: Dinsdale, NK
Izdano: (2021)

Bayesian quadrature for Gaussian process kernel learning, neural ensemble search, and high dimensional integrands
od: Hamid, S
Izdano: (2023)

Not So Robust after All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks
od: Roman Garaev, i dr.
Izdano: (2024-04-01)

AMAnD: an automated metagenome anomaly detection methodology utilizing DeepSVDD neural networks
od: Colin Price, i dr.
Izdano: (2023-07-01)

On Robustness of Neural Architecture Search Under Label Noise
od: Yi-Wei Chen, i dr.
Izdano: (2020-02-01)

Dysarthric-speech detection using transfer learning with convolutional neural networks
od: S R Mani Sekhar, i dr.
Izdano: (2022-03-01)

A one-dimensional convolutional neural network-based deep learning approach for predicting cardiovascular diseases
od: Dhafer G. Honi, i dr.
Izdano: (2024-01-01)

Convolutional Neural Networks in Detection of Plant Leaf Diseases: A Review
od: Bulent Tugrul, i dr.
Izdano: (2022-08-01)

Landslide Susceptibility Modeling Using a Deep Random Neural Network
od: Cheng Huang, i dr.
Izdano: (2022-12-01)

Enhancing adversarial robustness of quantum neural networks by adding noise layers
od: Chenyi Huang, i dr.
Izdano: (2023-01-01)

A deep neural network approach to predicting clinical outcomes of neuroblastoma patients
od: Tranchevent, Léon-Charles, i dr.
Izdano: (2021)

Deep neural network architectures for cardiac image segmentation
od: Jasmine El-Taraboulsi, i dr.
Izdano: (2023-12-01)

Web-Based Malware Detection System Using Convolutional Neural Network
od: Ali Alqahtani, i dr.
Izdano: (2023-09-01)

Deep learning approach with image noise reduction to determine planting density and defected paddy seedlings
od: Mohamed Anuar, Mohamed Marzhar
Izdano: (2022)

Graph neural networks for network analysis
od: He, Y
Izdano: (2024)