AI頂會NeurIPS 2019官方日前發布了論文接收的完整名單。官方發布的數據顯示，共計收到6743篇投稿，比去年的4856篇增長40%，論文接收量為1428篇，比去年的1011篇增長41%，接收率為20%。
另外，Oral論文共計接收36篇，佔比約為0.5%，Spotlight論文共計接收164篇，佔比約2.4%，二者比例均略微低於去年。
官方論文接收完整列表地址:
https://neurips.cc/Conferences/2019/AcceptedPapersInitial
（需手動複製打開，官方連結被舉報，不能跳轉(T_T)）
部分接收論文：
Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation
Risto Vuorio (University of Michigan) · Shao-Hua Sun (University of Southern California) · Hexiang Hu (University of Southern California) · Joseph Lim (University of Southern California)
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
Jiasen Lu (Georgia Tech) · Dhruv Batra (Georgia Tech / Facebook AI Research (FAIR)) · Devi Parikh (Georgia Tech / Facebook AI Research (FAIR)) · Stefan Lee (Georgia Institute of Technology)
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers
Liwei Wu (University of California, Davis) · Shuqing Li (University of California, Davis) · Cho-Jui Hsieh (UCLA) · James Sharpnack (UC Davis)
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video
Jiawang Bian (The University of Adelaide) · Zhichao Li (Tusimple) · Naiyan Wang (Hong Kong University of Science and Technology) · Huangying Zhan (The University of Adelaide) · Chunhua Shen (University of Adelaide) · Ming-Ming Cheng (Nankai University) · Ian Reid (University of Adelaide)
Zero-shot Learning via Simultaneous Generating and Learning
Hyeonwoo Yu (Seoul National University) · Beomhee Lee (Seoul National University)
Ask not what AI can do for you, but what AI should do: Towards a framework of task delegability
Brian Lubars (University of Colorado Boulder) · Chenhao Tan (University of Colorado Boulder)
Stand-Alone Self-Attention in Vision Models
Niki Parmar (Google) · Prajit Ramachandran (Google Brain) · Ashish Vaswani (Google Brain) · Irwan Bello (Google) · Anselm Levskaya (Google) · Jon Shlens (Google Research)
High Fidelity Video Prediction with Large Neural Nets
Ruben Villegas (Adobe Research / U. Michigan) · Arkanath Pathak (Google) · Harini Kannan (Google Brain) · Honglak Lee (Google / U. Michigan) · Dumitru Erhan (Google Brain) · Quoc V Le (Google)
Unsupervised learning of object structure and dynamics from videos
Matthias Minderer (Google Research) · Chen Sun (Google Research) · Ruben Villegas (Adobe Research / U. Michigan) · Forrester Cole (Google Research) · Kevin Murphy (Google) · Honglak Lee (Google Brain)
TensorPipe: Easy Scaling with Micro-Batch Pipeline Parallelism
Yanping Huang (Google Brain) · Youlong Cheng (Google) · Ankur Bapna (Google) · Orhan Firat (Google) · Dehao Chen (Google) · Mia Chen (Google Brain) · HyoukJoong Lee (Google) · Jiquan Ngiam (Google Brain) · Quoc V Le (Google) · Yonghui Wu (Google) · zhifeng Chen (Google Brain)
Meta-Learning with Implicit Gradients
Aravind Rajeswaran (University of Washington) · Chelsea Finn (Stanford University) · Sham Kakade (University of Washington) · Sergey Levine (UC Berkeley)
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas (MIT) · Shibani Santurkar (MIT) · Dimitris Tsipras (MIT) · Logan Engstrom (MIT) · Brandon Tran (Massachusetts Institute of Technology) · Aleksander Madry (MIT)