Chenjuan Guo
18 papers · 2019–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Academic Marathon (6) π Renaissance Researcher (6) π Conference Polyglot (8) πΊοΈ Taxonomy Completionist (33)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Conference Polyglot
(8)
π
Grand Slam
π€
Dynamic Duo
(15)
π±
Topic Pioneer
β‘
Prolific Year
(10)
π
Century Club
(16)
ποΈ
Keyword Collector
(55)
Conferences
ICLR (5)
AAAI (3)
ICML (3)
IJCAI (3)
CVPR (1)
ECCV (1)
EMNLP (1)
NIPS (1)
Top co-authors
Keywords
time series forecasting
(2)
unsupervised learning
(2)
transformer architecture
(1)
model quantization
(1)
adversarial learning
(1)
model selection
(1)
feature extraction
(1)
ai safety
(1)
curriculum learning
(1)
attention mechanism
(1)
knowledge transfer
(1)
knowledge distillation
(1)
network pruning
(1)
dialogue safety
(1)
graph representation
(1)
transfer learning
(1)
outlier detection
(1)
time series
(1)
neural network compression
(1)
model compression
(1)
Papers
Rethinking Irregular Time Series Forecasting: A Simple Yet Effective Baseline
AAAI 2026
Towards Non-Stationary Time Series Forecasting with Temporal Stabilization and Frequency Differencing
AAAI 2026
Enhancing Diversity for Data-free Quantization
CVPR 2025
MUSE: MCTS-Driven Red Teaming Framework for Enhanced Multi-Turn Dialogue Safety in Large Language Models
EMNLP 2025
Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems
ICLR 2025
Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders
ICLR 2025
CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching
ICLR 2025
Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation
ICLR 2025
Assessing Pre-Trained Models for Transfer Learning Through Distribution of Spectral Components
AAAI 2025
LightGTS: A Lightweight General Time Series Forecasting Model
ICML 2025
Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer
ICML 2025
$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
ICML 2025
Dependency-aware Differentiable Neural Architecture Search
ECCV 2024
Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
ICLR 2024
Weighted Mutual Learning with Diversity-Driven Model Compression
NIPS 2022
Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting
IJCAI 2022
Unsupervised Path Representation Learning with Curriculum Negative Sampling
IJCAI 2021
Outlier Detection for Time Series with Recurrent Autoencoder Ensembles
IJCAI 2019