Rumen Dangovski
According to our database1,
Rumen Dangovski
authored at least 35 papers
between 2018 and 2024.
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Collaborative distances:
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Bibliography
2024
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation.
CoRR, 2024
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024
2023
Representation Learning Through the Lens of Science: Symmetry, Language and Symbolic Inductive Biases
PhD thesis, 2023
Mitigating Confirmation Bias in Semi-supervised Learning via Efficient Bayesian Model Averaging.
Trans. Mach. Learn. Res., 2023
Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies.
CoRR, 2023
CoRR, 2023
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries.
Proceedings of the International Conference on Machine Learning, 2023
Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows.
Proceedings of the International Conference on Machine Learning, 2023
Contextualizing Enhances Gradient Based Meta Learning for Few Shot Image Classification.
Proceedings of the IEEE High Performance Extreme Computing Conference, 2023
Proceedings of the IEEE High Performance Extreme Computing Conference, 2023
Proceedings of the IEEE High Performance Extreme Computing Conference, 2023
Asymmetric Grouped Convolutions for Logarithmic Scale Efficient Convolutional Neural Networks.
Proceedings of the IEEE High Performance Extreme Computing Conference, 2023
2022
Koopman Operator learning for Accelerating Quantum Optimization and Machine Learning.
CoRR, 2022
CoRR, 2022
CoRR, 2022
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
CoRR, 2021
Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science.
CoRR, 2021
Adapting Deep Learning Models to New Meteorological Contexts Using Transfer Learning.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021
We Can Explain Your Research in Layman's Terms: Towards Automating Science Journalism at Scale.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Interpretable Neuroevolutionary Models for Learning Non-Differentiable Functions and Programs.
CoRR, 2020
On a Novel Application of Wasserstein-Procrustes for Unsupervised Cross-Lingual Learning.
CoRR, 2020
Vector-Vector-Matrix Architecture: A Novel Hardware-Aware Framework for Low-Latency Inference in NLP Applications.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
2019
Rotational Unit of Memory: A Novel Representation Unit for RNNs with Scalable Applications.
Trans. Assoc. Comput. Linguistics, 2019
2018
WaveletNet: Logarithmic Scale Efficient Convolutional Neural Networks for Edge Devices.
CoRR, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Improving the Performance of Unitary Recurrent Neural Networks and Their Application in Real-life Tasks.
Proceedings of the 19th International Conference on Computer Systems and Technologies, 2018