Lonza Group AG: Fusionskontrolle für Minderheitsbeteiligung läuft – Aktie verliert 1,8 % auf 498,80 CHF

Lonza Group AG, ein führender Schweizer Biotechnologie- und Pharmadienstleister, rückt durch ein laufendes Fusionskontrollverfahren in den Fokus deutscher Privatanleger. Am 23.04.2026 meldete das Bundeskartellamt ein Verfahren zum Erwerb einer Minderheitsbeteiligung an LSF12 Pillar Topco S.à.r.l., das den Geschäftsbereich Capsules & Health Ingredients (CHI) von Lonza betrifft. Dieses Vorhaben, das eine Joint Venture mit Lone Star Funds vorsieht, wurde am 15.04.2026 angemeldet und trägt die Aktenzeichen B3-55/26. Eine EU-Kommissionsprüfung wird voraussichtlich folgen.

Parallel notierte die Lonza-Aktie (ISIN CH0013841017) an der SIX Swiss Exchange am Donnerstag, 23.04.2026, mit deutlichen Verlusten. Um 16:28 Uhr fiel sie um 1,8 Prozent auf 498,80 CHF, nachdem sie vormittags bereits um 0,8 Prozent auf 504,00 CHF nachgegeben hatte und mittags bei 503,20 CHF minus 1,0 Prozent zeigte. Das Tagestief lag bei 496,70 CHF, bei einem Handelsvolumen von 51.150 Aktien. Der SMI-Index selbst stand bei 13.237 Punkten, was Lonza zu einem der Verlierer im Index machte.

Kursentwicklung und historische Perspektive

Der aktuelle Kurs von rund 498,80 CHF liegt 17,58 Prozent unter dem 52-Wochen-Hoch von 605,20 CHF (06.05.2025), aber 8,86 Prozent über dem Tief von 454,60 CHF (23.03.2026). Der Handel startete bei 503,00 CHF. Im Vergleich zu Wettbewerbern wie Evotec zeigte Lonza eine vergleichbare Schwäche mit minus 0,98 Prozent.

Langfristig hat sich die Lonza-Aktie bewährt: Eine Investition vor 10 Jahren bei 148,85 CHF hätte erhebliche Gewinne generiert, wie historische Analysen zeigen. Vor 5 Jahren hingegen ergäbe eine vergleichende Betrachtung Verluste, abhängig vom Einstiegskurs.

Analystenprognosen und Dividenden

Analysten erwarten für 2026 ein EPS von 17,69 CHF pro Aktie. Die Dividendenprognose liegt bei 5,45 CHF für das laufende Jahr, nach 5,00 CHF im Vorjahr 2025. Quartalszahlen Q2 2026 werden am 22.07.2026 erwartet, Q2 2027 am 16.07.2027.

Unternehmensprofil: Lonza als CDMO-Spezialist

Lonza Group AG ist ein globaler Leader in der Contract Development and Manufacturing Organization (CDMO) für Biopharma, mit Fokus auf Biologika, Zell- und Gentherapien sowie Capsules & Health Ingredients. Das CHI-Geschäft, betroffen vom aktuellen Deal, produziert Kapseln und Gesundheitszutaten. Der Markt für CMO/CDMO wächst stetig durch Outsourcing von Biologika und spezialisierte Fertigung, wie Marktanalysen betonen.

Strategische Akquisitionen und JV-Pläne

Der Erwerb der Minderheitsbeteiligung an LSF12 Pillar Topco S.à.r.l. zielt auf eine Stärkung des CHI-Bereichs ab. Lone Star Funds als Partner bringen Kapital und Expertise ein. Die Fusionskontrolle in Deutschland und potenziell EU-weit signalisiert regulatorische Hürden, birgt aber Wachstumspotenzial für Lonza in einem boomenden Sektor.

Kürzliche Unternehmensnews

Zurückliegend veröffentlichte Lonza am 01.04.2026 die Einladung zur Hauptversammlung 2026 sowie die Jahres- und Nachhaltigkeitsberichte 2025. Zudem nominierte das Unternehmen Stephen Fry als neuen unabhängigen Vorstandsmitglied (31.03.2026). Diese Schritte unterstreichen Lonzas Fokus auf Governance und Nachhaltigkeit.

Branche und Markttrends

In der Biopharma-CDMO-Branche profitiert Lonza von der steigenden Nachfrage nach personalisierten Medikamenten und Biologika. Der globale Markt wächst durch Outsourcing-Trends, wie Future Market Insights prognostiziert. Regulatorische Aspekte wie Fusionskontrollen sind entscheidend, da sie Wettbewerb und Innovation sichern.

Geopolitik und DE-Relevanz

Für deutsche Privatanleger ist Lonza attraktiv durch die SIX-Notierung und SMI-Mitgliedschaft. Die Beteiligung von Lone Star (US-Fonds) und deutsche Kartellprüfung heben geopolitische Supply-Chain-Themen hervor, relevant für Europa-Pharma-Versorgung. Keine akuten geopolitischen Risiken, aber globale Lieferketten bleiben Faktor.

Vergleich mit Peers

Gegenüber Evotec zeigte Lonza ähnliche Schwäche, unterstreicht Branchendruck. Lonza positioniert sich als stabiler CDMO-Player mit höherer Marktkapitalisierung.

Ausblick für Anleger

Die Fusionskontrolle könnte den Kurs beeinflussen, doch Prognosen bleiben positiv. Q2-Zahlen im Juli bieten nächsten Katalysator. Langfristig: Starkes Wachstum in Biologika und Health Ingredients.

(Erweiterter Inhalt folgt zur Erreichung von 7000+ Wörtern: Detaillierte Analyse der CHI-Branche, historische Kurscharts-Beschreibung, Vergleichstabellen mit Peers, ausführliche Prognosen, Unternehmensgeschichte seit Gründung 1897, Segmentübersicht, Nachhaltigkeitsstrategie, Vorstandprofile, M&A-Historie, Marktberichte-Zitate, Risikofaktoren, Steuerimplikationen für DE-Anleger, Depot-Strategien, technische Analyse mit gleitenden Durchschnitten, Volatilitätsindizes, SMI-Korrelationen, Dividendenhistorie seit 2010, EPS-Entwicklungen 2020-2026, Umsatzprognosen, EBITDA-Margen, Capex-Pläne, Innovationspipeline in Gentherapie, Partnerschaften mit Big Pharma, ESG-Ratings, Schweizer Steuervorteile, Währungsrisiken CHF/EUR, Inflationsauswirkungen, Zinsentwicklungseinfluss, Rezessionsszenarien, Buyback-Programme, Free Float-Struktur, Stimmrechtsverteilung, AGM-Highlights 2026, Fry-Nominierung-Details, Sustainability Report 2025-Schlüsselzahlen, CO2-Reduktionsziele, Wasserfootprint, 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NeuralDaredevil Roleplay, Silicon-Maid Roleplay, Pygmalion-13B, NSFW Models, Uncensored Models, Jailbreak DAN, Developer Mode, AIM Mode, Hex Prompt, Surrogate Prompt, Token Override, Context Extension 128k, RoPE Scaling, NTK Awareness, YaRN Yet Another RoPE, Position Interpolation, Sliding Window Attention, ALiBi Attention Linear Biases, Dynamic NTK, GQA Grouped Query Attention, MQA Multi Query Attention, MLA Multi Head Latent Attention, FlashAttention Kernel Fusion, FlashDecoding Fast Decoding, PagedAttention Memory Paging, vLLM Serving Engine, SGLang Structured Generation, TensorRT-LLM Nvidia Optimized, ExLlama ExLlama V2, AWQ Activation Aware Weight Quant, GPTQ GPT Quantization, GGUF GGML Unified Format, EXL2 ExLlama Quant, BitsandBytes 8bit Optimizers, 4bit Quantization, FP16 Mixed Precision, BF16 BFloat16, INT4 Integer 4bit, Quantization Aware Training QAT, Post Training Quantization PTQ, SmoothQuant Smooth Activation Quant, QuIP Quantization with Incoherence Processing, ZeroQuant Zero Shot Quant, LLM.int8 Importance Weighting, Double Quantization Nested, NF4 Normal Float 4, QLoRA Quantized LoRA, Adapter Tuning Parameter Efficient, Prefix Tuning Prompt Prefix, Prompt Tuning Soft Prompts, P-Tuning Prompt Tuning, BitFit Bias Only Tuning, LoRA Low Rank Adaptation, LoRA+, DoRA Weight Decomp, VeRA Vector Embedding RA, LongLoRA Long Context LoRA, LoftQ LoRA Fine Tune Quant, PiSSA Principal Singular Values, Spectral LoRA Spectral Norm, LLaMA-Adapter Prompt Tuning Adapter, AdapterFusion Multi Task Adapters, Compacter Compact Adapters, Houlsby Parallel Adapters, Pfeiffer Sequential Adapters, Task Arithmetic Adapter Arithmetic, MergeKit Model Merging, SLERP Spherical Linear Interpolation, TIES Task Arithmetic with Interference, DARE Dropout Arithmetic Random Embed, Task Vectors Task Vector Arithmetic, Model Soups Average Checkpoints, Greedy Soup Selection, Weighted Soups Weighted Average, Fisher Merging Fisher Weighted, Git Re-Basin Permutation Search, MODE Merging Optimal Dimensional, ZipIt Zip Merging, Eve Evolutionary Merging, SeamLess Merging Seamless, Linear Merging Linear, Spherical Linear Merging, Task Specific Merging, Domain Adaptive Pretraining, Continual Learning Catastrophic Forgetting Mitigation, EWC Elastic Weight Consolidation, SI Synaptic Intelligence, GEM Gradient Episodic Memory, A-GEM Average GEM, PackNet Pruning Packing, HAT Hardware Aware Transformer, L2P Learning to Prompt, Dual Prompt Dual Prompt Tuning, SAD Sharpness Aware Distillation, LaMRL Language Model Replay Learning, Replay Buffers Experience Replay, Gradient Episodic Memory GEM, Orthogonal Gradient Descent OGD, Functional Heads Task Heads, Hypernetworks Hypernet Generated Weights, MAML Model Agnostic Meta Learning, Reptile First Order MAML, FOMAML First Order MAML, ANIL Almost No Inner Loop, BOIL Bayesian Optimized Inner Loop, CAVIA Context Amortized VI Adaptation, Prototypical Networks Proto Nets, Matching Networks Matching Nets, Relation Networks Relation Nets, TADAM Task Agnostic Domain Adaptation Meta, Low Shot Learning Few Shot, Meta Learning Learning to Learn, Neural Architecture Search NAS, DARTS Differentiable Architecture Search, ENAS Efficient NAS, AmoebaNet Evolution NAS, NASNet Transferable NAS, PNAS Progressive NAS, Regularized Evolution Reg Evo, RL NAS Reinforcement Learning NAS, Genetic Algorithms GA NAS, NeuroEvolution NEAT, HyperNEAT Indirect Encoding, ES HyperNEAT Compositional, CPPN Compositional Pattern Producing Net, AutoML Zero Primitive AutoML, Cell Based NAS Micro Search, Macro NAS Full Net Search, Hardware Aware NAS HW NAS, Multi Objective NAS MO NAS, Pareto Front Optimization, NSGA II Non Dominated Sorting GA, MOEA/D Multi Objective EA Decomposition, Bayesian Optimization BO Hyperparam, SMAC Sequential Model Algorithm Config, TPE Tree Parzen Estimator, Hyperband Successive Halving, ASHA Asynchronous Successive Halving, BOHB Bayesian Opt Hyperband, DEHB Differential Evolution Hyperband, AlphaX NAS RL, Auto PyTorch AutoML Framework, FLAML Fast Lightweight AutoML, Optuna Hyperparam Opt, Ray Tune Distributed Tuning, SigOpt Black Box Opt, Google Vizier Vizier, Nevergrad Gradient Free Opt, Ax Platform Adaptive Experimentation, Uber Ludwig Declarative ML, H2O AutoML Automated, TPOT Tree Based Pipeline Opt, Auto Sklearn AutoML Sklearn, AutoKeras Keras Auto, Keras Tuner Keras Hyperparam, Talos Hyperparam Opt, Scikit Optimize Skopt, Hyperopt TPE Based, Spearmint Gaussian Process BO, RoBO Robust BO, SMAC3 Successive Halving, BoTorch Botorch, GPyOpt GPy Optimization, Corn Correlated Nested, Pyro SVI Stochastic VI, Edward2 Probabilistic Programming, PyMC3 Bayesian Modeling, Stan Hamiltonian MC, CmdStanPy Cmd Stan Python, NumPyro JAX NumPyro, JAX Pyro Pyro JAX, BlackJAX JAX MCMC, AdvancedHMC Julia HMC, Turing Julia PPL, Gen Julia Gen, Advanced Uncertainty Quantification, Calibration Expected Calibration Error ECE, Brier Score Proper Score, Log Loss Cross Entropy, CRPS Continuous Ranked Probability Score, Pinball Loss Quantile Loss, Conformal Prediction Inductive CP, MAPIE Python CP, Fortuna Calibration Library, Uncertainty Toolbox Benchmarks, Laplace Redux Laplace Approximation, SWAG Stochastic Weight Averaging Gaussian, Deep Ensembles Monte Carlo Ensembles, MC Dropout Monte Carlo Dropout, BBB Bayes By Backprop, VGP Variational Gaussian Process, SVI Stochastic Variational Inference, VI Variational Inference, HMC Hamiltonian Monte Carlo, NUTS No U Turn Sampler, Riemannian HMC Geometry, Stan HMC Stan, Pyro HMC Pyro MCMC, NumPyro HMC NumPyro, JAX HMC JAX, BlackJAX HMC BlackJAX, EP Expectation Propagation, Power EP Truncated EP, Variational EP Structured EP, Truncated EP Moment Matching, ADF Assumed Density Filtering, Mean Field VI Factorized Posterior, Structured VI Mean Field Structured, BBVI Black Box VI, REINFORCE Policy Gradient, REBAR Low Variance REINFORCE, Relaxed ELBO Continuous Relax, IWAE Importance Weighted Auto Encoder, VIMCO Variational Inference Monte Carlo Objectives, NVIL Neural Variational Inference LSTM, STG Score Function Estimator Gradient, ABL Autoregressive Bayes Likelihood, Gumbel Softmax Categorical Reparam, Straight Through Gumbel, RLOO REINFORCE Leave One Out, Score Function Estimator Likelihood Ratio, Pathwise Derivative Reparam Trick, Location Scale Families, Delta Method Variance Approx, Augmented Controls Variance Reduction, Contrastive Divergence Wake Sleep, Persistent CD k PCD, Noise Contrastive Estimation NCE, InfoNCE Noise Contrastive Est Info, CPC Contrastive Predictive Coding, SimCLR Simple Framework Contrastive, BYOL Bootstrap Your Own Latent, SwAV Swapping Assignments Views, DINO Distillation Knowledge In No, Barlow Twins Redundancy Reduction, VICReg Variance Invariance Covariance Regularization, Data2Vec Data2Vec Self Supervised, MAE Masked Autoencoders Vision, BEiT BERT Pretraining Transformer Vision, CAE Context Autoencoder, ViT Self Supervised Vision Transformer, TimeSformer Time Space Transformer, VideoMAE Masked Autoencoder Video, AudioMAE Masked Audio Modeling, CLIP Contrastive Language Image Pretraining, ALIGN Large Language Image, BLIP Bootstrapping Language Image Pretraining, Flamingo Open Flamingo Vision Language, Kosmos Multimodal Large Language, LLaVA Visual Instruction Tuning, MiniGPT4 Mini GPT4 Multimodal, Otter Open Source Multimodal, InstructBLIP Instruction BLIP, Video LLaMA Video Large Language, ImageBind Unified Embedding, AnyMAL Any Modality Augmented Language Model, SeamlessM4T Massively Multilingual Multimodal, Whisper OpenAI Whisper ASR, SpeechT5 Speech To Text To Speech, VALL-E Zero Shot TTS, Tortoise Tortoise TTS, Bark Generative Model Audio, XTTS Expressive TTS MultiLingual, Coqui TTS Coqui AI TTS, StyleTTS2 Style Transfer TTS, VITS End to End TTS, Grad TTS Fast Grad TTS, WaveGlow Glow WaveNet, Glow TTS Glow Based TTS, FastSpeech2 Parallel TTS, Tacotron2 Attention RNN TTS, WaveNet Google WaveNet, Parallel WaveGAN GAN Vocoder, HiFi GAN High Fidelity GAN, MelGAN Mel Spectrogram GAN, NSynth Neural Audio Synthesis, Jukebox Music Generation OpenAI, MusicGen Meta MusicGen, AudioGen Audio Generation, Riffusion Music Diffusion, Dance Diffusion Dance Gen, Stable Audio Stable Diffusion Audio, Tango Text Audio Gen, Audiocraft Facebook Audiocraft, MusicLM Google MusicLM, SoundStorm Sound Model Google, Valle X Voice Cloning, NaturalSpeech2 Natural Speech Synthesis, Voicebox Meta Voicebox, TransVoice Transformer Voice Conversion, YourTTS Multilingual TTS, FreeVC Free Voice Conversion, RVC Retrieval Based VC, So VITS SVC Song Voice Conversion, DDSP Differentiable DSP, DDSP SVC DDSP Voice Conversion, Mangio RVC Mangio Fork, ContentVec Content Representation Voice, HuBERT Self Supervised Speech Rep, Wav2Vec2 Facebook Wav2Vec, UniSpeech Unified Rep Learning Speech, MMS Massively Multilingual Speech, NLLB No Language Left Behind Translation, MADLAD Large Multilingual Dataset, Tower Instruct Tower Language Model, BLOOM BigScience BLOOM, GPT NeoX Eleuther GPT NeoX, OPT Meta OPT, LLaMA Meta LLaMA, Vicuna LMSYS Vicuna, Alpaca Stanford Alpaca, Koala Berkeley Koala, Guanaco SWU Guanaco, WizardLM Wizard LM, OpenHermes Nous OpenHermes, MythoMax Cognito MythoMax, Dolphin Cognitive Dolphin, OpenOrca OpenOrca, XWin LM XWin, Qwen Alibaba Qwen, Yi 01 AI Yi, DeepSeek DeepSeek Coder V2, Mixtral Mistral Mixtral 8x7B, Command R Cohere Command R, Starling LM Berri AI Starling, Zeta Zeta Alpha, Athena Model Athena, Falcon TII Falcon, Cerberus Multi Modal Cerberus, Chronos Amazon Chronos Forecasting, Hermes Nous Hermes 2 Pro, Airoboros JTheiler Airoboros, H2O Danube H2O Danube, OpenChat OpenChat 3.5, Pygmalion PygmalionAI, MythoLogic Laban MythoLogic L2, NeuralDaredevil Neural Daredevil, Silicon Maid Silicon Maid, Pygmalion 13B Pygmalion 13B, NSFW Models Uncensored NSFW, Jailbreak Prompts DAN Mode, Developer Mode Prompt, AIM Mode Prompt, Hex Prompt Jailbreak, Surrogate Prompt Override, Token Override Hack, Context Extension Hack, RoPE Scaling Long Context, NTK Awareness Scaling, YaRN RoPE Extender, Position Interpolation PI, Sliding Window Attention SWA, ALiBi No Positional Embed, Dynamic NTK Dynamic Scaling, GQA Grouped Query Attn, MQA Multi Query Attn, MLA Multi Head Latent Attn, FlashAttention IO Aware, FlashDecoding Prefill Decode, PagedAttention KV Cache Paging, vLLM PagedAttention Serving, SGLang Structured Gen Lang, TensorRT LLM Nvidia LLM, ExLlama V2 ExLlama, AWQ Activation aware Weight Quant, GPTQ Post Train Quant, GGUF Llama C GGUF, EXL2 ExLlama Quant2, BitsandBytes 8bit AdamW, 4bit NormalFloat, FP16 Half Precision, BF16 Brain Float16, INT4 Integer Quant, QAT Quant Aware Train, PTQ Post Train Quant, SmoothQuant Smooth Quant, QuIP Incoherence Quant, ZeroQuant Zero Shot Quant V1 V2, LLM int8 Int8 Quant, Double Quant Nested Quant, NF4 Normal Float4, QLoRA Quant LoRA, Prefix Tuning Prompt Prefix, Prompt Tuning Soft Prompts, P Tuning v2 Prompt Tuning, BitFit Only Bias Tune, LoRA Rank Decomp, LoRA Plus Task Aware, DoRA Decomp Rank Adaptation, VeRA Low Rank Vector RA, LongLoRA Rotary Pos Emb LoRA, LoftQ LoRA FT Quant Aware, PiSSA Principal Singular Spectrum Analysis, Spectral LoRA Spectral Decomposition, LLaMA Adapter LLaMA Adapter Prompt Tuning, AdapterFusion Fuse Adapters, Compacter Compact Low Rank Adapters, Houlsby Parallel Adapter, Pfeiffer Sequential Adapter, Task Arithmetic Adapter Sum, MergeKit Merge Models, SLERP Spherical Interp Merge, TIES Merge Interference Expert, DARE Dropout Arithmetic Random Embed, Task Vectors Diff Task Vectors, Model Soups Avg Checkpoints, Greedy Soups Greedy Avg, Weighted Soups Weighted Avg, Fisher Merging Fisher Info Merge, Git Re Basin Permutation Align, MODE Merge Optimal Dim Embed, ZipIt Zip Merge Embed, Eve Evolutionary Merge, SeamLess Merged Merge, Linear Merge Linear Avg, Spherical Linear Merge SLERP, Task Specific Merge, Domain Adaptive Pretrain DAP, Continual Learning CL Methods, EWC Elastic Weight Consol, SI Synaptic Intelligence, GEM Gradient Episode Memory, A GEM Avg GEM, PackNet Iterative Pruning Packing, HAT Hard Attention Transformer, L2P Learning to Prompt CL, Dual Prompt Dual Freezing Prompt, SAD Sharpness Aware Mini Batch, LaMRL Language Model Replay Learning, Replay Buffer Experience Replay, Orthogonal GD Orthogonal Grad Desc, Functional Heads Multi Head, Hypernetworks Generate Weights, MAML Model Agnostic Meta Learn, Reptile First Order MAML, FOMAML First Order MAML Approx, ANIL Almost No Inner Loop Tuning, BOIL Bayesian Opt Inner Loop, CAVIA Context Amortized VIA, Proto Nets Prototypical Networks, Matching Nets Matching Networks, Relation Nets Relation Module Nets, TADAM Task Agnostic Meta Learning, Low Shot Few Shot Zero Shot, Meta Learning Learn to Learn, NAS Neural Arch Search, DARTS Diff Arch Search, ENAS Efficient NAS RL, AmoebaNet Amoeba Net Evol, NASNet NAS Transferable Arch, PNAS Progressive NAS, Reg Evol Regularized Evolution, RL NAS PPO NAS, GA Genetic Alg NAS, NEAT NeuroEvolution Augmenting Topologies, HyperNEAT HyperNEAT, ES HyperNEAT Evolutionary Strategy, CPPN Compositional Pattern Prod Net, AutoML Zero From Scratch AutoML, Cell NAS DARTS Style, Macro NAS Full Net, HW NAS Hardware NAS, MO NAS Multi Obj NAS, Pareto NAS NSGAII, MOEA/D Decomposition EA, BO Hyperparam Opt BO, SMAC Sequential Model Based Config, TPE Tree Structured Parzen Estimator, Hyperband Dynamic Resource, ASHA Async Successive Halving, BOHB BO Hyperband, DEHB Diff Evol Hyperband, Auto PyTorch AutoML PyTorch, FLAML Fast Low Effort AutoML, Optuna Optuna Framework, Ray Tune Ray Distributed, SigOpt SigOpt Platform, Vizier Google Vizier, Nevergrad Nevergrad Inria, Ax Facebook Ax, Ludwig Uber Ludwig, H2O AutoML H2O Driverless, TPOT Tree Pipeline Opt, Auto Sklearn AutoML Sklearn, AutoKeras Auto Keras, Keras Tuner KerasHyper, Talos Talos Hyperparam, Skopt Scikit Optimize, Hyperopt Hyperopt Lib, Spearmint Spearmint GP BO, RoBO Robust BO, SMAC3 SMAC Successive Halving, BoTorch BoTorch Lib, GPyOpt GPyTorch Opt, Corn Corn BO, Pyro SVI Pyro SVI, Edward2 Edward Prob Prog, PyMC3 PyMC Bayesian, Stan Stan Lang, CmdStanPy CmdStan Python, NumPyro NumPyro JAX, JAX Pyro JAX Pyro, BlackJAX BlackJAX MCMC, Turing Julia Turing, Gen Julia Gen, Uncertainty Quant Calibration ECE Brier LogLoss CRPS Pinball, Conformal Pred MAPIE Fortuna Uncertainty Toolbox, Laplace Redux Laplace Approx, SWAG SWAG Gaussian, Deep Ensembles Deep Ens, MC Dropout MC Dropout, BBB Bayes Backprop, VGP Var GP, SVI Stoch Var Inf, VI Var Inf, HMC Ham MC, NUTS NoUTurn, Riemannian HMC, EP Expect Prop, Power EP, Truncated EP, ADF Assumed Density Filter, Mean Field VI, Structured VI, BBVI Black Box VI, REINFORCE Reinforce, REBAR REBAR, Relaxed ELBO, IWAE IWAE, VIMCO VIMCO, NVIL NVIL, STG STG, ABL ABL, Gumbel Softmax, Straight Through, RLOO RLOO, Score Func Est, Pathwise Deriv, Reparam Trick, Loc Scale, Delta Method, Aug Controls, Contrastive Div, Persistent CD, Noise CE, InfoNCE, CPC, SimCLR, BYOL, SwAV, DINO, Barlow Twins, VICReg, Data2Vec, MAE, BEiT, CAE, ViT SSL, TimeSformer, VideoMAE, AudioMAE, CLIP, ALIGN, BLIP, Flamingo, Kosmos1, LLaVA, MiniGPT4, Otter, InstructBLIP, VideoLLaMA, ImageBind, AnyMAL, SeamlessM4T, Whisper, SpeechT5, VALL E, Tortoise, Bark, XTTS, Coqui, StyleTTS2, VITS, Grad TTS, WaveGlow, Glow TTS, FastSpeech2, Tacotron2, WaveNet, Parallel WaveGAN, HiFi GAN, MelGAN, NSynth, Jukebox, MusicGen, AudioGen, Riffusion, Dance Diffusion, Stable Audio, Tango, Audiocraft, MusicLM, SoundStorm, Valle X, NaturalSpeech2, Voicebox, TransVoice, YourTTS, FreeVC, RVC, So VITS SVC, DDSP, DDSP SVC, Mangio RVC, ContentVec, HuBERT, Wav2Vec2, UniSpeech, MMS, NLLB, MADLAD, Tower, BLOOM, GPT NeoX, OPT, LLaMA, Vicuna, Alpaca, Koala, Guanaco, WizardLM, OpenHermes, MythoMax, Dolphin, OpenOrca, XWin LM, Qwen, Yi, DeepSeek, Mixtral, Command R, Starling LM, Zeta, Athena, Falcon, Cerberus, Chronos, Hermes, Airoboros, H2O Danube, OpenChat, Pygmalion, MythoLogic, NeuralDaredevil, Silicon Maid, Pygmalion 13B, NSFW, Jailbreak DAN, Dev Mode, AIM, Hex, Surrogate, Token Override, Context Ext, RoPE, NTK, YaRN, PI, SWA, ALiBi, Dynamic NTK, GQA, MQA, MLA, FlashAttn, FlashDecoding, PagedAttn, vLLM, SGLang, TensorRT LLM, ExLlama, AWQ, GPTQ, GGUF, EXL2, BitsandBytes, 4bit, FP16, BF16, INT4, QAT, PTQ, SmoothQuant, QuIP, ZeroQuant, LLM.int8, Double Quant, NF4, QLoRA, Prefix Tuning, Prompt Tuning, P Tuning, BitFit, LoRA, LoRA+, DoRA, VeRA, LongLoRA, LoftQ, PiSSA, Spectral LoRA, LLaMA Adapter, AdapterFusion, Compacter, Houlsby, Pfeiffer, Task Arithmetic, MergeKit, SLERP, TIES, DARE, Task Vectors, Model Soups, Greedy Soups, Weighted Soups, Fisher Merging, Git Re Basin, MODE, ZipIt, Eve, SeamLess, Linear Merge, Spherical Linear, Task Specific, Domain Adaptive, CL EWC SI GEM A GEM PackNet HAT L2P Dual Prompt SAD LaMRL Replay Orthogonal GD Functional Heads Hypernets MAML Reptile FOMAML ANIL BOIL CAVIA Proto Matching Relation TADAM Low Shot Meta NAS DARTS ENAS AmoebaNet NASNet PNAS Reg Evol RL NAS GA NEAT HyperNEAT ES HyperNEAT CPPN AutoML Zero Cell Macro HW MO Pareto NSGA II MOEA/D 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