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portfolio
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publications
Multimodal Distributions in Variational Autoencoders
Published in MSc Thesis at Skoltech, 2017
Recommended citation: E. Iakovleva. "Multimodal Distributions in Variational Autoencoders." MSc Thesis at Skoltech, 2017.
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Exploring Generative Image Modeling with Block PixelCNNs
Published in MSc Thesis at Grenoble INP, 2018
Recommended citation: E. Iakovleva. "Exploring Generative Image Modeling with Block PixelCNNs." MSc Thesis at Grenoble INP, 2018.
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Meta-Learning with Shared Amortized Variational Inference
Published in International Conference on Machine Learning, 2020
Recommended citation: E. Iakovleva, J. Verbeek and K. Alahari. "Meta-Learning with Shared Amortized Variational Inference." In ICML'20.
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Multi-Domain Learning with Modulation Adapters
Published in arXiv, 2023
Recommended citation: E. Iakovleva, K. Alahari and J. Verbeek. "Multi-Domain Learning with Modulation Adapters." In arXiv:2307.08528'23.
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Specify and Edit: Overcoming Ambiguity in Text-Based Image Editing
Published in British Machine Vision Conference, 2025
Recommended citation: E. Iakovleva, F. Pizzati, P. Torr and S. Lathuilière. "Specify and Edit: Overcoming Ambiguity in Text-Based Image Editing." In BMVC'25.
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How I Met Your Bias: Investigating Bias Amplification in Diffusion Models
Published in IEEE/CVF Winter Conference on Applications of Computer Vision, 2026
Recommended citation: N. Roos, E. Iakovleva, A. Gjergji, V. Pastore and E. Tartaglione. "How I Met Your Bias: Investigating Bias Amplification in Diffusion Models." In WACV'26.
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Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2026
Recommended citation: I. Matos, A. Saoud, E. Iakovleva, V. Pastore and E. Tartaglione. "Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models." In CVPR'26.
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talks
Meta-Learning at ICML’20
Published:
Video presentation of the paper “Meta-Learning with Shared Amortized Variational Inference” at the International Conference on Machine Learning 2020.
Text-Based Image Editing at BMVC’25
Published:
Video presentation of the paper “Specify and Edit: Overcoming Ambiguity in Text-Based Image Editing” at the British Machine Vision Conference 2025.
teaching
Deep Learning for Computer Vision
Master course, Télécom Paris, 2024
TP (lab) sessions “Domain Adaptation” and “CLIP”, final exam with grading.
Deep Leaning for Multimedia
Master course, Télécom Paris, 2024
Lecture on Transformers and Transfer Learning.
Introduction to Deep Learning
Master course, Télécom Paris, 2025
TP (laboratory) session “Convolutional Neural Networks (CNNs)” and lab grading.
Practice in Deep Learning
Master course, ATHENS, 2025
TP (laboratory) sessions “Introduction to Python and MLPs” and “Convolutional Neural Networks (CNNs)”, lab grading.
Deep Leaning for Multimedia
Master course, Télécom Paris, 2025
Lecture on Recurrent Neural Networks (RNNs) and Transformers.