Innervu Knowledge Navigator

Deep Generative Imputation Model for Missing Not At Random Data

By J. Chen et al
Published on June 10, 2023

Hardware Accelerator for Adversarial Attacks on Deep Learning Neural Networks

By H. Guo et al
Published on None

Masked Contrastive Representation Learning

By Y. Yao et al
Published on None

An Improved Genetic Algorithm and Its Application in Neural Network Adversarial Attack

By Dingming Yang et al.
Published on None

Foiling Explanations in Deep Neural Networks

By Snir Vitrack et al
Published on Aug. 10, 2023

Boosting Adversarial Attacks on Neural Networks with Better Optimizer

By H. Yin et al
Published on None

Detect Any Deepfakes

By Y. Lai et al
Published on June 29, 2023

MART: Improving LLM Safety with Multi-round Automatic Red-Teaming

By S. Ge et al
Published on Nov. 13, 2023

Exploring Adversarial Attacks on Neural Networks: An Explainable Approach

By Justus Renkhoff et al
Published on None

Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method

By Yu-An Liu et al
Published on Oct. 21, 2023

Continual Learning for Generative Retrieval over Dynamic Corpora

By Jiangui Chen et al.
Published on Oct. 21, 2023

Generating Synthetic Documents for Cross-Encoder Re-Rankers: A Comparative Study of ChatGPT and Human Experts

By Arian Askari et al
Published on May 3, 2023

Manifold Matching via Deep Metric Learning for Generative Modeling

By M. Dai et al
Published on None

Adversarial Attacks on Spiking Convolutional Neural Networks for Event-based Vision

By Julian B., et al
Published on None

Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies

By Wei Jiny et al
Published on None

I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation

By Chandra Bhagavatula et al.
Published on May 26, 2023

A Review of Adversarial Attacks in Computer Vision

By Zhang Y. et al
Published on Aug. 15, 2023

An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks

By R. Lapid et al.
Published on None

Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey

By Wei Emma Zhang et al
Published on April 10, 2019

Pfgm++: Unlocking the Potential of Physics-Inspired Generative Models

By Yilun Xu et al
Published on None

Patch of Invisibility: Naturalistic Physical Black-Box Adversarial Attacks on Object Detectors

By R. Lapid et al
Published on Oct. 17, 2023

Multimodal Deep Learning

By Matthias Aßenmacher et al
Published on Jan. 12, 2023

A Comprehensive Evaluation Framework for Deep Model Robustness

By Jun G. et al
Published on Nov. 2, 2022

Towards Understanding the Mechanism of Contrastive Learning via Similarity Structure: A Theoretical Analysis

By H. Waida et al
Published on None

Technology Trends Outlook 2023

By McKinsey & Company et al
Published on July 10, 2023

Quantum Neural Networks

By Kerstin Beer et al
Published on May 17, 2022

Adversarial Attacks and Defences: A Survey

By Anirban Chakraborty et al
Published on Sept. 28, 2018