NIPS Papers

[Neural Information Processing Systems (NIPS)](https://nips.cc/) is one of the top machine learning conferences in the world. It covers topics ranging from deep learning and computer vision to cognitive science and reinforcement learning.

This dataset includes the title, authors, abstracts, and extracted text for all NIPS papers to date (ranging from the first 1987 conference to the current 2016 conference). I've extracted the paper text from the raw PDF files and are releasing that both in CSV files and as a SQLite database. The code to scrape and create this dataset is [on GitHub](https://github.com/benhamner/nips-papers). Here's a [quick RMarkdown exploratory overview of what's in the data](https://www.kaggle.com/benhamner/d/benhamner/nips-papers/exploring-the-nips-papers).
[](https://www.kaggle.com/benhamner/d/benhamner/nips-papers/popular-datasets-over-time)
We encourage you to explore this data and share what you find through Kaggle Kernels!

神经信息处理系统会议（Neural Information Processing Systems，简称 NIPS）系全球顶尖的机器学习盛会之一。该会议涵盖的主题范围广泛，从深度学习与计算机视觉，至认知科学和强化学习等均有涉及。本数据集包含了自 1987 年首届会议至今（截至 2016 年会议）所有 NIPS 论文的标题、作者、摘要及提取文本。论文文本已从原始 PDF 文件中提取，并以 CSV 文件和 SQLite 数据库的形式发布。用于抓取和创建此数据集的代码可在 GitHub 上找到（https://github.com/benhamner/nips-papers）。此外，提供了一份简要的 RMarkdown 探索性概述，以展示数据集的内容（https://www.kaggle.com/benhamner/d/benhamner/nips-papers/exploring-the-nips-papers）。[](https://www.kaggle.com/benhamner/d/benhamner/nips-papers/popular-datasets-over-time)。我们鼓励您深入探索这些数据，并通过 Kaggle Kernels 分享您的发现！