3 citations · 3 across the 2 of their papers we have counts for
5 papers · 1 filter
TabDPT: Scaling Tabular Foundation Models on Real Data
Junwei Ma, Valentin Thomas, Rasa Hosseinzadeh +7
Tabular data is one of the most ubiquitous sources of information worldwide, spanning a wide variety of domains. This inherent heterogeneity has slowed the development of Tabular F…
Retrieval & Fine-Tuning for In-Context Tabular Models
Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh +4
Tabular data is a pervasive modality spanning a wide range of domains, and the inherent diversity poses a considerable challenge for deep learning. Recent advancements using transf…
Data-Efficient Multimodal Fusion on a Single GPU
Noël Vouitsis, Zhaoyan Liu, Satya Krishna Gorti +5
The goal of multimodal alignment is to learn a single latent space that is shared between multimodal inputs. The most powerful models in this space have been trained using massive…
Self-supervised Representation Learning From Random Data Projectors
Yi Sui, Tongzi Wu, Jesse C. Cresswell +5
Self-supervised representation learning~(SSRL) has advanced considerably by exploiting the transformation invariance assumption under artificially designed data augmentations. Whil…
MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting
Linfeng Du, Ji Xin, Alex Labach +3
Transformer-based models have greatly pushed the boundaries of time series forecasting recently. Existing methods typically encode time series data into using on…