{
  "originalData": {
    "name": "Al in Drug Discovery Companies Focus on Oncology: Leadership by Funding Level",
    "startPoint": 20,
    "data": {
      "AI": {
        "Classical ML": {
          "Gradient Boosting": {
            "Gradient Tree Boosting": "2001",
            "XGBoost": "2016",
            "LightGBM": "2017",
            "CatBoost": "2018"
          }
        },
        "Reinforcement Learning": {
          "Trust Region Policy Optimization (TRPO)": "2015",
          "Deep Q-Network (DQN)": "2015",
          "Double DQN": "2016",
          "Dueling DQN": "2016",
          "Advantage Actor-Critic (A2C)": "2016",
          "Asynchronous Advantage Actor-Critic (A3C)": "2016",
          "Soft Actor-Critic (SAC)": "2018"
        },
        "Supervised/Unsupervised Learning": {
          "Neural Network Based Algorithms": {
            "Convolutional Neural Networks (ConvNets, CNNs)": {
              "Image Processing Networks": {
                "LeNet": "1998",
                "AlexNet": "2012",
                "VGG": "2014",
                "GoogLeNet (Inception)": "2014",
                "ResNet": "2015",
                "DenseNet": "2016",
                "MobileNet": "2017",
                "ImageNet": "2017",
                "EfficientNet": "2019",
                "EfficientNetV2": "2020",
                "Vision Transformer (ViT)": "2020",
                "ResNeSt": "2020",
                "Swin Transformer": "2021",
                "CrossViT": "2021"
              },
              "Video Processing": {
                "3D CNN": "2012",
                "Two-Steam CNN": "2014",
                "Two-Steam CNN with Fusion": "2016",
                "Temporal Segment CNN": "2016",
                "You Look Only Once (YOLO)": "2016",
                "R(2+1)D": "2018"
              }
            },
            "Recurrent neural networks": {
              "Long Short-Term Memory (LSTM)": "1997",
              "Bidirectional RNN (BRNN)": "1997",
              "Echo State Network (ESN)": "2002",
              "Gated Recurrent Unit (GRU)": "2014",
              "RNNsearch": "2014",
              "Hierarchical RNN (HRNN)": "2015",
              "Recurrent Convolutional Neural Network (RCNN)": "2015",
              "UGRNN": "2015",
              "QRNN": "2016",
              "GNMT": "2016",
              "AWD-LSTM": "2018",
              "SRU": "2018"
            },
            "Autoencoders": {
              "Denoising Autoencoder": "2008",
              "Convolutional Autoencoder": "2011",
              "Contractive Autoencoder": "2011",
              "Variational Autoencoder": "2013",
              "Adversarial Autoencoder": "2015"
            },
            "Transformers": {
              "Vanilla Transformer": "2017",
              "BERT (Bidirectional Encoder Representations from Transformers)": "2018",
              "XLNet": "2019"
            },
            "Language Models (LM)": {
              "Neural Language Models": {
                "Neural language model": "2003"
              },
              "Pre-trained Language Models": {
                "Embeddings from Language Models (ELMo)": "2018",
                "RoBERTa (Robustly Optimized BERT Pretraining Approach)": "2019",
                "Bidirectional Encoder Representations from Transformers (BERT)": "2018",
                "GPT (Generative Pre-trained Transformer)": "2018",
                "GPT-2": "2019",
                "BART": "2019"
              },
              "Large Language Models": {
                "T5 (Text-to-Text Transfer Transformer)": "2019",
                "GPT-3": "2020",
                "LaMDA": "2022",
                "PaLM": "2022",
                "Galactica": "2022",
                "GPT-4": "2023",
                "LLaMA": "2023"
              }
            },
            "Generative adversarial networks": {
              "Vanilla GAN": "2014",
              "Conditional GAN": "2014",
              "Wasserstein GAN (WGAN)": "2017",
              "CycleGAN": "2017",
              "Progressive GAN": "2017",
              "StarGAN": "2017"
            },
            "Diffusion models": {
              "Diffusion Probabilistic Model": "2015",
              "Noise-conditioned Score Network": "2019",
              "Denoising diffusion probabilistic model": "2020",
              "Latent Diffusion Model": "2022"
            },
            "Siamese Neural Networks": {
              "Basic Siamese network": "2005",
              "Triple network": "2015",
              "Quadruple network": "2017",
              "RNN-based Siamese network": "2017",
              "Multi-view Siamese network": "2018",
              "Pseudo Siamese network": "2018",
              "GNN-based Siamese network": "2019",
              "Siamese GAN": "2019",
              "Manifold-based Siamese network": "2019",
              "Cross-modal Siamee network": "2019",
              "DenseDisp": "2020"
            },
            "Graph neural networks": {
              "Recurrent Graph Neural Networks": {
                "Graph Neural Network": "2005",
                "Graph Echo State Networks (GraphESN)": "2010",
                "Graph Attention Network": "2017"
              },
              "Convolutional Graph Neural Networks": {
                "Spectral-based Convolutional Graph Neural Network": "2014",
                "Diffusion-convolutional Graph Neural Network": "2016"
              },
              "Graph Autoencoders": {
                "Network Embeddings": {
                  "Graph Autoencoder": "2016",
                  "Variational Graph Auto-Encoders": "2016",
                  "Adversarially Regularized Graph Autoencoder": "2018"
                },
                "Graph Generation": {
                  "GraphRNN": "2018",
                  "GraphVAE": "2018",
                  "NetGAN": "2018"
                }
              },
              "Spatial-temporal Graph Neural Networks": {
                "Structural-RNN": "2016",
                "Graph WaveNet": "2018",
                "Spatio-Temporal Graph Convolutional Networks": "2018",
                "Attention Based Spatial-Temporal Graph Convolutional Networks": "2019"
              }
            }
          }
        }
      }
    }
  }
}