Tianbao Yang

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All published works

Action	Title	Year	Authors
+ PDF Chat	Advanced graph and sequence neural networks for molecular property prediction and drug discovery	2022	Zhengyang Wang Meng Liu Youzhi Luo Xu Zhao Yaochen Xie Limei Wang Lei Cai Qi Qi Zhuoning Yuan Tianbao Yang

Common Coauthors

Coauthor	Papers Together
Youzhi Luo	1
Shuiwang Ji	1
Lei Cai	1
Qi Qi	1
Xu Zhao	1
Meng Liu	1
Zhengyang Wang	1
Limei Wang	1
Zhuoning Yuan	1
Yaochen Xie	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Ranking and combining multiple predictors without labeled data	2014	Fabio Parisi Francesco Strino Boaz Nadler Yuval Kluger	1
+ PDF Chat	On representing chemical environments	2013	Albert P. Bartók Risi Kondor Gábor Cśanyi	1
+ PDF Chat	Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons	2010	Albert P. Bartók M. C. Payne Risi Kondor Gábor Cśanyi	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+ PDF Chat	Molecular graph convolutions: moving beyond fingerprints	2016	Steven Kearnes Kevin McCloskey Marc Berndl Vijay S. Pande Patrick Riley	1
+ PDF Chat	Quantum-chemical insights from deep tensor neural networks	2017	Kristof T. Schütt Farhad Arbabzadah Stefan Chmiela K. Müller Alexandre Tkatchenko	1
+ PDF Chat	MoleculeNet: a benchmark for molecular machine learning	2017	Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes Caleb Geniesse Aneesh Pappu Karl Leswing Vijay S. Pande	1
+	SMILES Enumeration as Data Augmentation for Neural Network Modeling of Molecules	2017	Esben Jannik Bjerrum	1
+	Junction Tree Variational Autoencoder for Molecular Graph Generation	2018	Wengong Jin Regina Barzilay Tommi Jaakkola	1
+	Relational inductive biases, deep learning, and graph networks	2018	Peter Battaglia Jessica B. Hamrick Victor Bapst Álvaro Sánchez‐González Vinícius Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner	1
+	Gaussian Error Linear Units (GELUs)	2016	Dan Hendrycks Kevin Gimpel	1
+ PDF Chat	PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges	2019	Oliver T. Unke Markus Meuwly	1
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	1
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	1
+	Analyzing Learned Molecular Representations for Property Prediction	2019	Kevin Yang Kyle Swanson Wengong Jin Connor W. Coley Philipp Eiden Hua Gao Angel Guzmán-Pérez Timothy Hopper Brian P. Kelley Miriam Mathea	1
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	1
+	SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery	2019	Shion Honda Shoi Shi Hiroki R. Ueda	1
+	wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations	2020	Alexei Baevski Henry Zhou Abdelrahman Mohamed Michael Auli	1
+	Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence.	2021	Qi Qi Youzhi Luo Xu Zhao Shuiwang Ji Tianbao Yang	1
+	Benchmarking Graph Neural Networks	2020	Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu Laurent Thomas Yoshua Bengio Xavier Bresson	1