10 citations · 14 across the 13 of their papers we have counts for
8 papers · 1 filter
From News to Returns: A Granger-Causal Hypergraph Transformer on the Sphere
Anoushka Harit, Zhongtian Sun, Jongmin Yu
We propose the Causal Sphere Hypergraph Transformer (CSHT), a novel architecture for interpretable financial time-series forecasting that unifies \emph{Granger-causal hypergraph st…
Quantifying Semantic Shift in Financial NLP: Robust Metrics for Market Prediction Stability
Zhongtian Sun, Chenghao Xiao, Anoushka Harit +1
Financial news is essential for accurate market prediction, but evolving narratives across macroeconomic regimes introduce semantic and causal drift that weaken model reliability.…
EWC-Guided Diffusion Replay for Exemplar-Free Continual Learning in Medical Imaging
Anoushka Harit, William Prew, Zhongtian Sun +1
Medical imaging foundation models must adapt over time, yet full retraining is often blocked by privacy constraints and cost. We present a continual learning framework that avoids…
RicciFlowRec: A Geometric Root Cause Recommender Using Ricci Curvature on Financial Graphs
Zhongtian Sun, Anoushka Harit
We propose RicciFlowRec, a geometric recommendation framework that performs root cause attribution via Ricci curvature and flow on dynamic financial graphs. By modelling evolving i…
ManifoldMind: Dynamic Hyperbolic Reasoning for Trustworthy Recommendations
Anoushka Harit, Zhongtian Sun, Suncica Hadzidedic
We introduce ManifoldMind, a probabilistic geometric recommender system for exploratory reasoning over semantic hierarchies in hyperbolic space. Unlike prior methods with fixed cur…
GLANCE: Graph Logic Attention Network with Cluster Enhancement for Heterophilous Graph Representation Learning
Zhongtian Sun, Anoushka Harit, Alexandra Cristea +2
Graph Neural Networks (GNNs) have demonstrated significant success in learning from graph-structured data but often struggle on heterophilous graphs, where connected nodes differ i…
Causal Spherical Hypergraph Networks for Modelling Social Uncertainty
Anoushka Harit, Zhongtian Sun
Human social behaviour is governed by complex interactions shaped by uncertainty, causality, and group dynamics. We propose Causal Spherical Hypergraph Networks (Causal-SphHN), a p…
Actionable Interpretability via Causal Hypergraphs: Unravelling Batch Size Effects in Deep Learning
Zhongtian Sun, Anoushka Harit, Pietro Lio
While the impact of batch size on generalisation is well studied in vision tasks, its causal mechanisms remain underexplored in graph and text domains. We introduce a hypergraph-ba…