Search Results for author: Tongtao Zhang

Found 13 papers, 1 papers with code

A Neural ODE Interpretation of Transformer Layers

no code implementations12 Dec 2022 Yaofeng Desmond Zhong, Tongtao Zhang, Amit Chakraborty, Biswadip Dey

Our experiments show that this simple modification improves the performance of transformer networks in multiple tasks.

Image Classification Numerical Integration

Demystifying the Data Need of ML-surrogates for CFD Simulations

no code implementations5 May 2022 Tongtao Zhang, Biswadip Dey, Krishna Veeraraghavan, Harshad Kulkarni, Amit Chakraborty

Computational fluid dynamics (CFD) simulations, a critical tool in various engineering applications, often require significant time and compute power to predict flow properties.

Frequency-compensated PINNs for Fluid-dynamic Design Problems

no code implementations3 Nov 2020 Tongtao Zhang, Biswadip Dey, Pratik Kakkar, Arindam Dasgupta, Amit Chakraborty

We demonstrate this approach by predicting simulation results over out of range time interval and for novel design conditions.

Training with Streaming Annotation

no code implementations11 Feb 2020 Tongtao Zhang, Heng Ji, Shih-Fu Chang, Marjorie Freedman

In this paper, we address a practical scenario where training data is released in a sequence of small-scale batches and annotation in earlier phases has lower quality than the later counterparts.

Event Extraction

Visualizing Group Dynamics based on Multiparty Meeting Understanding

no code implementations EMNLP 2018 Ni Zhang, Tongtao Zhang, Indrani Bhattacharya, Heng Ji, Rich Radke

Group discussions are usually aimed at sharing opinions, reaching consensus and making good decisions based on group knowledge.

Decision Making Opinion Mining +1

Seq2RDF: An end-to-end application for deriving Triples from Natural Language Text

3 code implementations4 Jul 2018 Yue Liu, Tongtao Zhang, Zhicheng Liang, Heng Ji, Deborah L. McGuinness

Inspired by recent successes in neural machine translation, we treat the triples within a given knowledge graph as an independent graph language and propose an encoder-decoder framework with an attention mechanism that leverages knowledge graph embeddings.

Decoder Knowledge Graph Embeddings +1

Event Extraction with Generative Adversarial Imitation Learning

no code implementations21 Apr 2018 Tongtao Zhang, Heng Ji

We propose a new method for event extraction (EE) task based on an imitation learning framework, specifically, inverse reinforcement learning (IRL) via generative adversarial network (GAN).

Event Extraction Feature Engineering +3

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