Innervu Knowledge Navigator

A Comprehensive Survey on Graph Neural Networks

By Z. Wu et al.
Published on Aug. 10, 2019

A Survey of Deep Active Learning

By Pengzhen Ren et al
Published on Dec. 5, 2021

Selecting the Best Optimizers for Deep Learning Based Medical Image Segmentation

By Aliasghar Mortazia et al
Published on Feb. 5, 2023

Contextuality and Inductive Bias in Quantum Machine Learning

By Joseph B et al
Published on April 18, 2023

Completely Quantum Neural Networks

By Steve Abel et al
Published on None

On the Symmetries of Deep Learning Models and Their Internal Representations

By Charles Godfrey et al
Published on None

Hidden Technical Debt in Machine Learning Systems

By D. Sculley et al
Published on None

Convolutional Neural Fabrics

By Shreyas Saxena et al
Published on Jan. 30, 2017

Learning To Optimize Quantum Neural Network Without Gradients

By Ankit Kulshrestha et al
Published on None

Deep Sets

By Manzil Zaheer et al
Published on April 14, 2018

An Invitation to Distributed Quantum Neural Networks

By Lirande Pira et al
Published on Nov. 15, 2022

A Comprehensive Survey on Transfer Learning

By F. Zhuang et al
Published on June 23, 2020

A Survey On Deep Neural Network Compression

By Rahul Mishra et al
Published on Oct. 5, 2020

A Neural Network Based Method with Transfer Learning for Genetic Data Analysis

By J. Lin et al
Published on Aug. 10, 2015

Towards Understanding Mixture of Experts in Deep Learning

By Z. Chen et al.
Published on Aug. 4, 2022

Graph Matching Networks for Learning the Similarity of Graph Structured Objects

By Y. Li et al
Published on June 10, 2019

Supervised Contrastive Learning

By Prannay Khosla et al
Published on March 10, 2021

Curriculum Learning

By Yoshua Bengio et al
Published on June 10, 2009

Learning to Rank

By Hongning Wang et al
Published on None

A Review of Deep Transfer Learning and Recent Advancements

By Mohammadreza Iman et al
Published on Dec. 22, 2022

Learning Transferable Architectures for Scalable Image Recognition

By Barret Zoph et al
Published on None

Personalization of Deep Learning

By Johannes Schneider et al
Published on None

Learning Loss for Active Learning

By D. Yoo et al
Published on May 9, 2019

Neural Arithmetic Logic Units

By Andrew Trask et al
Published on Aug. 1, 2018

The Implicit and Explicit Regularization Effects of Dropout

By Colin Wei et al
Published on June 10, 2020

Quantum Computing Lecture

By Anuj Dawar et al
Published on None

Deep Convolutional Neural Network Design Patterns

By Leslie N. Smith et al
Published on None

Quantum Neural Networks: Concepts, Applications, and Challenges

By Y. Kwak et al
Published on None

Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels

By X. You et al
Published on March 28, 2023

A Comprehensive Survey of Continual Learning: Theory, Method and Application

By Liyuan Wang et al
Published on Aug. 10, 2015

The Power of Ensembles for Active Learning in Image Classification

By William H. Beluch et al
Published on None

An Introduction to Matrix Factorization and Factorization Machines in Recommendation System, and Beyond

By Yuefeng Zhang et al
Published on March 12, 2022

Debiased Contrastive Learning

By Ching-Yao Chuang et al
Published on Oct. 21, 2020

Deep Learning for Time Series Classification: A Review

By H. I. Fawaz et al
Published on None

What Is the State of Neural Network Pruning?

By Davis Blalock et al.
Published on March 6, 2020

The Principles of Deep Learning Theory

By Daniel A. Roberts et al
Published on Aug. 24, 2021

Learning by Turning: Neural Architecture Aware Optimisation

By Yang Liu et al
Published on Sept. 18, 2021

Multi-domain Recommendation with Embedding Disentangling and Domain Alignment

By W. Ning et al
Published on Oct. 21, 2025

DeepSpeed Data Efficiency

By Conglong Li et al
Published on June 10, 2024

Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning

By Charles H. Martin et al
Published on Oct. 2, 2018

Enabling Deep Learning on Edge Devices

By Zhongnan Qu et al
Published on Oct. 6, 2022

TabNet: Attentive Interpretable Tabular Learning

By Sercan ¨O. Arık et al
Published on None

Self-Supervised Multi-Modal Sequential Recommendation

By K. Song et al
Published on None

Physics-Based Deep Learning

By N. Thuerey et al
Published on April 25, 2022

Deep Task-Specific Bottom Representation Network for Multi-Task Recommendation

By Qi Liu et al
Published on Oct. 21, 2023

On Empirical Comparisons of Optimizers for Deep Learning

By Dami C. et al
Published on None

STDP-Based Spiking Deep Convolutional Neural Networks for Object Recognition

By Saeed Reza Kheradpisheh et al
Published on June 10, 2017

BOHB: Robust and Efficient Hyperparameter Optimization at Scale

By Stefan Falkner et al
Published on June 10, 2018

Efficient and Quantum-Adaptive Machine Learning with Fermion Neural Networks

By Pei-Lin Zheng et al
Published on Sept. 19, 2023

A Learning Method for Optimization with Hard Constraints

By Priya L. Donti et al
Published on April 25, 2021

What Learning Algorithm Is In-Context Learning? Investigations with Linear Models

By Ekin Akyurek et al
Published on May 17, 2023

Findings of the Association for Computational Linguistics: ACL 2023

By Zhiying Jiang et al
Published on July 9, 2014

Ensemble Deep Learning: A Review

By M. A. Ganaie et al.
Published on None

Neural Tensor Factorization

By X. Wu et al
Published on June 10, 2018

Deep Multi-view Learning to Rank

By G. Cao et al
Published on None

A Survey on Ensemble Learning under the Era of Deep Learning

By Y. Yang et al
Published on None

Harmonic (Quantum) Neural Networks

By Atiyo Ghosh et al.
Published on June 10, 2023

PolyNet: A Pursuit of Structural Diversity in Very Deep Networks

By X. Zhang et al
Published on July 17, 2017

Decentralized Graph Neural Network for Privacy-Preserving Recommendation

By X. Zheng et al
Published on June 10, 2023

Deep Meta-learning in Recommendation Systems: A Survey

By Chunyang Wang et al
Published on Aug. 10, 2018

Gradient-Based Learning Applied to Document Recognition

By Yann LeCun et al
Published on Nov. 10, 1998

Post-Hoc Selection of Pareto-Optimal Solutions in Search and Recommendation

By V. Paparella et al
Published on June 21, 2023

Quantum Neural Network for Quantum Neural Computing

By Min-Gang Zhou et al
Published on May 16, 2023

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems

By Benjamin Coleman et al
Published on None

Graph Neural Networks: A Review of Methods and Applications

By J. Zhou et al.
Published on None

When Do Flat Minima Optimizers Work?

By Jean Kaddour et al
Published on None

Afastlearningalgorithm fordeepbeliefnets

By Geoffrey E. Hinton et al
Published on June 10, 2006

ImageNet Classification with Deep Convolutional Neural Networks

By Alex Krizhevsky et al
Published on None

Dropout: A Simple Way to Prevent Neural Networks from Overfitting

By Nitish Srivastava et al
Published on June 10, 2014

CS294a Lecture Notes Andrew Ng Sparse Autoencoder

By Andrew Ng et al
Published on None

Tensor Programs IVb: Adaptive Optimization In The ∞-Width Limit

By Greg Yang et al
Published on Aug. 7, 2023

Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering

By Xi Wu et al
Published on Oct. 21, 2023

L2R: Lifelong Learning for First-Stage Retrieval with Backward-Compatible Representations

By Y. Cai et al
Published on Oct. 21, 2023

Meta-Learning In Neural Networks: A Survey

By T. Hospedales et al.
Published on Nov. 7, 2020

Ieee Signal Processing Magazine, Special Issue On Deep Learning For Image Understanding

By Y. Cheng et al.
Published on None

A Universal Law Of Robustness Via Isoperimetry

By Sébastien Bubeck et al
Published on Dec. 23, 2022

Out Of The Box Thinking: Improving Customer Lifetime Value Modelling Via Expert Routing And Game Whale Detection

By Shijie Zhang et al
Published on Oct. 21, 2023

A Survey of Deep Learning Optimizers - First and Second Order Methods

By Rohan V Kashyap et al
Published on Aug. 10, 2023

Pointnet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

By Charles R. Qi et al
Published on June 7, 2017

Pruning Vs Quantization: Which Is Better?

By Andrey K et al
Published on None

Inductive Representation Learning on Large Graphs

By William L. Hamilton et al
Published on None

Deep Learning for Genomics: A Concise Overview

By Tianwei Yue et al
Published on Oct. 4, 2023