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Lakshya Singhal

3 accepted papers

2023

Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?

ICML 2023oral

An important milestone for AI is the development of algorithms that can produce drawings that are indistinguishable from those of humans. Here, we adapt the ''diversity vs. recognizability'' scoring framework from Boutin et al (2022) and find that one-shot diffusion models have indeed started to clo…

2023

Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-Encoders

AISTATS 2023poster

Class imbalance is a common phenomenon in multiple application domains such as healthcare, where the sample occurrence of one or few class categories is more prevalent in the dataset than the rest. This work addresses the class-imbalance issue by proposing an over-sampling method for the minority cl…

2022

Diversity vs. Recognizability: Human-like generalization in one-shot generative models

NeurIPS 2022accept

Robust generalization to new concepts has long remained a distinctive feature of human intelligence. However, recent progress in deep generative models has now led to neural architectures capable of synthesizing novel instances of unknown visual concepts from a single training example. Yet, a more p…