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PennML Benchmark Suite
The PennML benchmark suite consists of over 90 regression problems and provides a performance overview of several common regression algorithms. -
CEC2013 Benchmark Functions
The dataset used in this paper is the CEC2013 benchmark functions. -
Guard: A safe reinforcement learning benchmark
The dataset used in the paper is a collection of robot locomotion tasks with various constraints. -
Building a conversational agent overnight with dialogue self-play
The Building a conversational agent overnight with dialogue self-play dataset is a benchmark for conversational AI. -
AI-Feynman database
The AI-Feynman database is a widely used public benchmark for symbolic regression. -
Keijzer benchmark
The Keijzer benchmark is a widely used public benchmark for symbolic regression. -
Nguyen benchmark
The Nguyen benchmark is a widely used public benchmark for symbolic regression. -
OpenAI Gym’s Mujoco benchmark
The dataset used in this paper is a set of demonstrations for reinforcement learning, containing safe and unsafe trajectories. -
Benchmark Graphs for Testing Community Detection Algorithms
The LFR benchmark is a collection of artificial networks with a known community structure. -
TrackingNet: A large-scale dataset and benchmark for object tracking in the wild
The authors proposed a large-scale benchmark for object tracking in the wild. -
LaSOT: A high-quality large-scale single object tracking benchmark
The authors proposed a large-scale benchmark for object tracking in the wild. -
VisDrone-SOT2019
The VisDrone-SOT2019 dataset is a large-scale drone benchmark for single object tracking. -
WIDER FACE: A face detection benchmark
WIDER FACE: A face detection benchmark.