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While most generative models show achievements in image data generation, few are developed for tabular data generation.
Visualizing data using t-SNE
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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The synthetic data vault
Neha Patki, Roy Wedge, and Kalyan Veeramachaneni · 2016
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Wasserstein Generative Adversarial Networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Generating multi-label discrete patient records using generative adversarial networks
Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter Stewart, and Jimeng Sun · 2017
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Real-valued (medical) time series generation with Recurrent Conditional GANs
Cristóbal Esteban, Stephanie Hyland, and Gunnar Rätsch · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Lightgbm: A highly efficient gradient boosting decision tree
Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu · 2017
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A unified approach to interpreting model predictions
Scott Lundberg and Su-In Lee · 2017
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VeeGAN: Reducing mode collapse in gans using implicit variational learning
Akash Srivastava, Lazar Valkov, Chris Russell, Michael Gutmann, and Charles Sutton · 2017
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Table-to-text: Describing table region with natural language
Junwei Bao, Duyu Tang, Nan Duan, Zhao Yan, Yuanhua Lv, Ming Zhou, and Tiejun Zhao · 2018
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Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation
Shivapratap Gopakumar, Sunil Gupta, Santu Rana, Vu Nguyen, and Svetha Venkatesh · 2018
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Data Synthesis Based on Generative Adversarial Networks
Noseong Park, Mahmoud Mohammadi, Kshitij Gorde, Sushil Jajodia, Hongkyu Park, and Youngmin Kim · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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SciBERT: A Pretrained Language Model for Scientific Text
Iz Beltagy, Kyle Lo, and Arman Cohan · 2019
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Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, and Ruslan Salakhutdinov · 2019
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PATE-GAN: Generating synthetic data with differential privacy guarantees
James Jordon, Jinsung Yoon, and Mihaela Van Der Schaar · 2019
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An introduction to variational autoencoders
Diederik Kingma, Max Welling, et al · 2019
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A Multiscale Visualization of Attention in the Transformer Model
Jesse Vig · 2019
Cited alongside, same era.
Modeling tabular data using Conditional GAN
Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni · 2019
Cited alongside, same era.
RPT: relational pre-trained transformer is almost all you need towards democratizing data preparation
Nan Tang, Ju Fan, Fangyi Li, Jianhong Tu, Xiaoyong Du, Guoliang Li, Sam Madden, and Mourad Ouzzani · 2021
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Balancing sequential data to predict students at-risk using adversarial networks
Hajra Waheed, Muhammad Anas, Saeed-Ul Hassan, Naif Radi Aljohani, Salem Alelyani, Ernest Edem Edifor, and Raheel Nawaz · 2021
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Table-To-Text generation and pre-training with TabT5
Ewa Andrejczuk, Julian Eisenschlos, Francesco Piccinno, Syrine Krichene, and Yasemin Altun · 2022
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Deep neural networks and tabular data: A survey
Vadim Borisov, Tobias Leemann, Kathrin Seßler, Johannes Haug, Martin Pawelczyk, and Gjergji Kasneci · 2022
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Black-box few-shot knowledge distillation
Dang Nguyen, Sunil Gupta, Kien Do, and Svetha Venkatesh · 2022
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Insaf Ashrapov · 2020
Cited alongside, same era.
TabFact : A Large-scale Dataset for Table-based Fact Verification
Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, and Yang Wang · 2020
Cited alongside, same era.
TaPas: Weakly Supervised Table Parsing via Pre-training
Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, Francesco Piccinno, and Julian Eisenschlos · 2020
Cited alongside, same era.
Reformer: The efficient transformer
Nikita Kitaev, Łukasz Kaiser, and Anselm Levskaya · 2020
Cited alongside, same era.
Conditional tabular GAN-based two-stage data generation scheme for short-term load forecasting
Jaeuk Moon, Seungwon Jung, Sungwoo Park, and Eenjun Hwang · 2020
Cited alongside, same era.
Reliable fidelity and diversity metrics for generative models
Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, and Jaejun Yoo · 2020
Cited alongside, same era.
Bayesian optimization for categorical and category-specific continuous inputs
Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, and Svetha Venkatesh · 2020
Cited alongside, same era.
Amirarsalan Rajabi and Ozlem Ozmen Garibay · 2022
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Tabular data: Deep learning is not all you need
Ravid Shwartz-Ziv and Amitai Armon · 2022
Later among the works it cites.
Differentially private synthetic medical data generation using Convolutional GANs
Amirsina Torfi, Edward Fox, and Chandan Reddy · 2022
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Language models are realistic tabular data generators
Vadim Borisov, Kathrin Seßler, Tobias Leemann, Martin Pawelczyk, and Gjergji Kasneci · 2023
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Tabllm: Few-shot classification of tabular data with large language models
Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, and David Sontag · 2023
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Synthcity: facilitating innovative use cases of synthetic data in different data modalities
Zhaozhi Qian, Bogdan-Constantin Cebere, and Mihaela van der Schaar · 2023
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Generative table pre-training empowers models for tabular prediction
Tianping Zhang, Shaowen Wang, Shuicheng Yan, Jian Li, and Qian Liu · 2023
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TabMT: Generating tabular data with masked transformers
Manbir Gulati and Paul Roysdon · 2024
Closest in time.
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in ultra low-data regimes
Nabeel Seedat, Nicolas Huynh, Boris van Breugel, and Mihaela van der Schaar · 2024
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Table meets LLM: Can large language models understand structured table data? a benchmark and empirical study
Yuan Sui, Mengyu Zhou, Mingjie Zhou, Shi Han, and Dongmei Zhang · 2024
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Language-interfaced tabular oversampling via progressive imputation and self-authentication
June Yong Yang, Geondo Park, Joowon Kim, Hyeongwon Jang, and Eunho Yang · 2024
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