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Results for: Svetha Venkatesh

Graph Transformation Policy Network for Chemical Reaction Prediction

K. Do, T. Tran, S. Venkatesh

2019 / pp. (Accepted 30 Apr 2019) / Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)

Learning to Remember More with Less Memorization

H. Le, T. Tran, S. Venkatesh

2019 / pp. (Accepted 21 Dec 2018) / International Conference on Learning Representations (ICLR)

Attentional multilabel learning over graphs: a message passing approach

K. Do, T. Tran, T. Nguyen, S. Venkatesh

2019 / pp. 1 - 25 / Machine Learning

Explaining Black-box Machine Learning Models using Interpretable Surrogates

D. Kuttichira, S. Gupta, R. Santu, C. Li, S. Venkatesh

2019 / pp. (to appear) / Pacific Rim International Conference on Artificial Intelligence

Bayesian functional optimisation with shape prior

P. Vellanki, S. Rana, S. Gupta, D. Leal, A. Sutti, M. Height, S. Venkatesh

2019 / pp. (Accepted 1 Nov 2018) / The AAAI Conference on Artificial Intelligence (AAAI)

Improving Generalization and Stability of Generative Adversarial Networks

H. Thanh-Tung, T. Tran, S. Venkatesh

2019 / pp. (Accepted 21 Dec 2018) / International Conference on Learning Representations (ICLR)

A flexible transfer learning framework for Bayesian optimization with convergence guarantee

T. Joy, S. Rana, S. Gupta, S. Venkatesh

2019 / Vol. 115, pp. 656 - 672 / Expert Systems with Applications

Learning regularity in skeleton trajectories for anomaly detection in videos

R. Morais, V. Le, T. Tran, B. Saha, M. Mansour, S. Venkatesh

2019 / IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Multi-Target Optimisation via Bayesian Optimisation and Linear Programming

A. Shilton, S. Rana, S. Gupta, S. Venkatesh

2018 / UAI 2018: Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence

Filtering Bayesian optimization approach in weakly specified search space

V. Nguyen, S. Gupta, S. Rana, C. Li, S. Venkatesh

2018 / pp. 1 - 29 / Knowledge and Information Systems

Differentially Private Prescriptive Analytics

H. Harikumar, S. Rana, S. Gupta, T. Nguyen, R. Kaimal, S. Venkatesh

2018 / pp. 995 - 1000 / 2018 IEEE International Conference on Data Mining (ICDM)

LTARM: A novel temporal association rule mining method to understand toxicities in a routine cancer treatment

D. Nguyen, W. Luo, D. Phung, S. Venkatesh

2018 / Vol. 161, pp. 313 - 328 / Knowledge-Based Systems

Neural reasoning for chemical-chemical interaction

T. Pham, T. Tran, S. Venkatesh

2018 / NeurIPS 2018 Workshop on Machine Learning for Molecules and Materials

Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets

D. Nguyen, T. Nguyen, W. Luo, S. Venkatesh

2018 / pp. 361 - 372 / Pacific-Asia Conference on Knowledge Discovery and Data Mining

On catastrophic forgetting and mode collapse in Generative Adversarial Networks

H. Thanh-Tung, T. Tran, S. Venkatesh

2018 / ICML Workshop on Theoretical Foundations and Applications of Deep Generative Models

Jointly predicting affective and mental health scores using deep neural networks of visual cues on the Web

H. Nguyen, V. Nguyen, T. Nguyen, M. Larsen, B. O'Dea, D. Thanh, T. Le, D. Phung, S. Venkatesh, H. Christensen

2018 / Proceedings of the International Conference on Web Information Systems Engineering (WISE)

Accelerating Experimental Design by Incorporating Experimenter Hunches.

C. Li, S. Rana, S. Gupta, V. Nguyen, S. Venkatesh, A. Sutti, C. de, T. Slezak, M. Height, M. Mohammed, O.

2018 / pp. 257 - 266 / 2018 IEEE International Conference on Data Mining (ICDM)