22 citations · 41 across the 8 of their papers we have counts for
8 papers
3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers
Zai Shi, Zhao Meng, Yiran Xing +2
3D reconstruction aims to reconstruct 3D objects from 2D views. Previous works for 3D reconstruction mainly focus on feature matching between views or using CNNs as backbones. Rece…
SEA: Graph Shell Attention in Graph Neural Networks
Christian M. M. Frey, Yunpu Ma, Matthias Schubert
A common issue in Graph Neural Networks (GNNs) is known as over-smoothing. By increasing the number of iterations within the message-passing of GNNs, the nodes' representations of…
APPTeK: Agent-Based Predicate Prediction in Temporal Knowledge Graphs
Christian M. M. Frey, Yunpu Ma, Matthias Schubert
In temporal Knowledge Graphs (tKGs), the temporal dimension is attached to facts in a knowledge base resulting in quadruples between entities such as (Nintendo, released, Super Mar…
TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting
Haohai Sun, Jialun Zhong, Yunpu Ma +2
Temporal knowledge graph (TKG) reasoning is a crucial task that has gained increasing research interest in recent years. Most existing methods focus on reasoning at past timestamps…
The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decoding
Volker Tresp, Sahand Sharifzadeh, Hang Li +2
We present a unified computational theory of an agent's perception and memory. In our model, perception, episodic memory, and semantic memory are realized by different operational…
Adaptive Multi-Resolution Attention with Linear Complexity
Yao Zhang, Yunpu Ma, Thomas Seidl +1
Transformers have improved the state-of-the-art across numerous tasks in sequence modeling. Besides the quadratic computational and memory complexity w.r.t the sequence length, the…
Temporal Knowledge Graph Forecasting with Neural ODE
Zhen Han, Zifeng Ding, Yunpu Ma +2
There has been an increasing interest in inferring future links on temporal knowledge graphs (KG). While links on temporal KGs vary continuously over time, the existing approaches…
Causal Inference under Networked Interference and Intervention Policy Enhancement
Yunpu Ma, Volker Tresp
Estimating individual treatment effects from data of randomized experiments is a critical task in causal inference. The Stable Unit Treatment Value Assumption (SUTVA) is usually ma…