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Found 8 papers, 0 papers with code
Beyond Kalman Filters: Deep Learning-Based Filters for Improved Object Tracking
We further propose a new cost function for associating observations with tracks.
Ranked #2 on
Multi-Object Tracking
on SportsMOT
(using extra training data)
Intrinsically motivated option learning: a comparative study of recent methods
Options represent a framework for reasoning across multiple time scales in reinforcement learning (RL).
Neural Algorithmic Reasoners are Implicit Planners
We find that prior approaches either assume that the environment is provided in such a tabular form -- which is highly restrictive -- or infer "local neighbourhoods" of states to run value iteration over -- for which we discover an algorithmic bottleneck effect.
FAIR: Fair Adversarial Instance Re-weighting
In this paper we propose a Fair Adversarial Instance Re-weighting (FAIR) method, which uses adversarial training to learn instance weighting function that ensures fair predictions.
XLVIN: eXecuted Latent Value Iteration Nets
Value Iteration Networks (VINs) have emerged as a popular method to incorporate planning algorithms within deep reinforcement learning, enabling performance improvements on tasks requiring long-range reasoning and understanding of environment dynamics.
Hierachial Protein Function Prediction with Tails-GNNs
Protein function prediction may be framed as predicting subgraphs (with certain closure properties) of a directed acyclic graph describing the hierarchy of protein functions.
Gaussian Conditional Random Fields for Classification
The extended method of local variational approximation of sigmoid function is used for solving empirical Bayes in Bayesian GCRFBCb variant, whereas MAP value of latent variables is the basis for learning and inference in the GCRFBCnb variant.
Short Portfolio Training for CSP Solving
However, there is no single solver (nor approach) that performs well on all classes of problems and many portfolio approaches for selecting a suitable solver based on simple syntactic features of the input CSP instance have been developed.
