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Bhattacharya, S., Arya, D., Bhowmick, D., Thomas, R. M., & Gupta, D. K. (2021). Improving Solar Cell Metallization Designs using Convolutional Neural Networks. In Deep Learning for Simulation (SimDL) workshop: International Conference on Learning Representations
Cardenas, B., Arya, D., & Gupta, D. K. (2021). Generating Annotated High-Fidelity Images Containing Multiple Coherent Objects. In 2021 IEEE International Conference on Image Processing: proceedings : 19-22 September 2021, Anchorage, Alaska, USA (pp. 834-838). (ICIP). IEEE. https://doi.org/10.1109/ICIP42928.2021.9506406[details]
Gupta, D. K., Arya, D., & Gavves, E. (2021). Rotation Equivariant Siamese Networks for Tracking. In Proceedings, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition: virtual, 9-25 June 2021 (pp. 12357-12366). (CVPR). Conference Publishing Services, IEEE Computer Society. https://doi.org/10.48550/arXiv.2012.13078, https://doi.org/10.1109/CVPR46437.2021.01218[details]
Tangirala, B., Bhandari, I., Laszlo, D., Gupta, D. K., Thomas, R. M., & Arya, D. (2021). Livestock Monitoring with Transformer. In British Machine Vision Conference
2020
Arya, D., Olij, R., Gupta, D. K., El Gazzar, A., van Wingen, G., Worring, M., & Thomas, R. M. (2020). Fusing Structural and Functional MRIs using Graph Convolutional Networks for Autism Classification. Proceedings of Machine Learning Research, 121, 44-61. http://proceedings.mlr.press/v121/arya20a.html[details]
Kuipers, T. P., Arya, D., & Gupta, D. K. (2020). Hard Occlusions in Visual Object Tracking. In A. Bartoli, & A. Fusiello (Eds.), Computer Vision – ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 : proceedings (Vol. V, pp. 299-314). (Lecture Notes in Computer Science; Vol. 12539). Springer. https://doi.org/10.1007/978-3-030-68238-5_22[details]
2019
Arya, D., Rudinac, S., & Worring, M. (2019). HyperLearn: A Distributed Approach for Representation Learning in Datasets With Many Modalities. In MM'19: proceedings of the 27th ACM Conference on Multimedia : October 21-25, 2019, Nice, France (pp. 2245-2253). Association for Computing Machinery. https://doi.org/10.1145/3343031.3350572[details]
Arya, D., Rudinac, S., & Worring, M. (2019). Predicting Behavioural Patterns in Discussion Forums using Deep Learning on Hypergraphs. In C. Gurrin, B. Þ. Jónsson, R. Péteri, S. Rudinac, S. Marchand-Maillet, G. Quénot, K. McGuinness, G. Þ. Guðmundsson, S. Little, M. Katsurai, & G. Healy (Eds.), 2019 International Conference on Content-Based Multimedia Indexing (CBMI): proceedings : September 4-6, 2019, held at: DCU All Hallows Campus, Dublin 9, Ireland (pp. 210-215). IEEE. https://doi.org/10.1109/CBMI.2019.8877384[details]
Ibrahimi, S., Chen, S., Arya, D., Câmara, A., Chen, Y., Crijns, T., van der Goes, M., Mensink, T., van Miltenburg, E., Odijk, D., Thong, W., Zhao, J., & Mettes, P. (2019). Interactive Exploration of Journalistic Video Footage through Multimodal Semantic Matching. In MM'19: proceedings of the 27th ACM Conference on Multimedia : October 21-25, 2019, Nice, France (pp. 2196-2198). Association for Computing Machinery. https://doi.org/10.1145/3343031.3350597[details]
2018
Arya, D., & Worring, M. (2018). Exploiting Relational Information in Social Networks using Geometric Deep Learning on Hypergraphs. In ICMR'18: proceedings of the 2018 ACM International Conference on Multimedia Retrieval : June 11-14, 2018, Yokohama, Japan (pp. 117-125). The Association for Computing Machinery. https://doi.org/10.1145/3206025.3206062[details]
2022
Arya, D. (2022). Multimodal deep learning on hypergraphs. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
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