conftrace_

Deep Learning

66,648 papers (25 classified directly here)

Subtopics

Learning Types (28,663) Architectures (27,448) Models (16,617) Techniques (8,241) Optimization & Theory (6,829) Application Areas (46)

Papers per year

2
65
428
6150
10854
'05
'10
'15
'20
'25

Papers (including subtopics)

DeepExposure: Learning to Expose Photos with Asynchronously Reinforced Adversarial Learning NIPS 2018
Insights on representational similarity in neural networks with canonical correlation NIPS 2018
Evidential Deep Learning to Quantify Classification Uncertainty NIPS 2018
Frequency-Domain Dynamic Pruning for Convolutional Neural Networks NIPS 2018
Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems NIPS 2018
Towards Text Generation with Adversarially Learned Neural Outlines NIPS 2018
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network NIPS 2018
Conditional Adversarial Domain Adaptation NIPS 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks NIPS 2018
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise NIPS 2018
Multi-Task Zipping via Layer-wise Neuron Sharing NIPS 2018
Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching NIPS 2018
Learning to Multitask NIPS 2018
Thwarting Adversarial Examples: An $L_0$-Robust Sparse Fourier Transform NIPS 2018
Generative modeling for protein structures NIPS 2018
Reparameterization Gradient for Non-differentiable Models NIPS 2018
SimplE Embedding for Link Prediction in Knowledge Graphs NIPS 2018
REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis NIPS 2018
Latent Alignment and Variational Attention NIPS 2018
On the Local Hessian in Back-propagation NIPS 2018
Constrained Graph Variational Autoencoders for Molecule Design NIPS 2018
Learning Disentangled Joint Continuous and Discrete Representations NIPS 2018
Recurrent Relational Networks NIPS 2018
Transfer Learning with Neural AutoML NIPS 2018
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs NIPS 2018