DEEP LEARNING FOR SYMBOLIC MATHEMATICS
https://arxiv.org/pdf/1912.01412.pdf
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
http://nscl.csail.mit.edu/data/papers/2019ICLR-NSCL.pdf
MODERN AI/ML
https://truyentran.github.io/talks/ML2019.pdf
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
http://proceedings.mlr.press/v70/finn17a/finn17a.pdf
Self-Supervised Representation Learning
https://lilianweng.github.io/lil-log/2019/11/10/self-supervised-learning.html
AutoAugment:Learning Augmentation Strategies from Data
https://arxiv.org/pdf/1805.09501.pdf
An Automated Framework for the Extraction of SemanticLegal Metadata from Legal Texts
https://arxiv.org/pdf/2001.11245.pdf
Towards Deep Machine Reasoning: a Prototype-based Deep Neural Network with Decision TreeInference
https://arxiv.org/pdf/2002.03776.pdf
GAMEPAD: A LEARNING ENVIRONMENT FOR THEOREM PROVING
https://arxiv.org/pdf/1806.00608.pdf
Graph-Based Global Reasoning Networks
https://arxiv.org/pdf/1811.12814.pdf
Universal-RCNN: Universal Object Detector via Transferable Graph R-CNN
https://arxiv.org/pdf/2002.07417.pdf
Self-training with Noisy Student improves ImageNet classification
https://arxiv.org/pdf/1911.04252.pdf
Hierarchical Rule Induction Network for Abstract Visual Reasoning
https://arxiv.org/pdf/2002.06838.pdf
Chronofold: a data structure for versioned text
https://arxiv.org/pdf/2002.09511.pdf
Using Supervised Learning to Classify Metadata ofResearch Data by Discipline of Research
https://arxiv.org/pdf/1910.09313.pdf
Objects as Points
https://arxiv.org/pdf/1904.07850v2.pdf
Do Better ImageNet Models Transfer Better?
Fixing the train-test resolution discrepancy
https://arxiv.org/pdf/1906.06423.pdf
Convolutional Character Networks
https://arxiv.org/pdf/1910.07954.pdf
Class-Balanced Loss Based on Effective Number of Samples
https://arxiv.org/pdf/1901.05555.pdf
Efficient Backbone Search for Scene Text Recognition
https://arxiv.org/pdf/2003.06567.pdf
Mapping the landscape of Artificial Intelligence applicationsagainst COVID-19
https://arxiv.org/pdf/2003.11336.pdf
Generative Language Modeling for AutomatedTheorem Proving
https://arxiv.org/pdf/2009.03393.pdf
A (Slightly) Improved Approximation Algorithm for Metric TSP
https://arxiv.org/abs/2007.01409
ProtTrans: Towards Cracking the Language of Life’s Code Through Self-Supervised Deep Learning and High Performance Computing
https://www.biorxiv.org/content/10.1101/2020.07.12.199554v2.full.pdf
High-Quality Protein Force Fields with Noisy Quantum Processors
https://arxiv.org/pdf/1907.07128.pdf
Dynamic ReLU
https://arxiv.org/pdf/2003.10027.pdf
Effective Dimensionality Reduction for Word Embeddings
https://www.aclweb.org/anthology/2020.acl-main.726.pdf
VoroCNN: Deep convolutional neural network built on 3D Voronoi tessellation of protein structures
https://www.biorxiv.org/content/10.1101/2020.04.27.063586v1.full.pdf
Deep Graph Generators: A Survey